- Ruhr-Universität Bochum

Following nature's example, there is currently strong interest in using adenosine 5′-triphosphate (ATP) as a fuel for the self-assembly of functional materials with transient/non-equilibrium behaviours. These hold great promise for applications, e.g. in catalysis and drug delivery. In a recent seminal work [Maiti et al., Nat. Chem., 2016, 8, 725], binding of ATP to the metallosurfactant zinc hexadecyl-1,4,7-triazacyclononane ([ZnC16 TACN]2+) was exploited to produce ATP-fueled transient vesicles. Crucial to the complex formation is the ability of ATP to bind to the metal ion. As a first step to unveil the key elements underlying this process, we investigate the interaction of ATP with Zn2+ and with methyl-1,4,7-triazacyclononane ([ZnCH3 TACN]2+), using all-atom molecular dynamics simulations. The free energy landscape of the complex formation is sampled using well-tempered metadynamics with three collective variables, corresponding to the coordination numbers of Zn2+ with the oxygen atoms of the three phosphate groups. We find that the structure of the ternary complex is controlled by direct triphosphate coordination to zinc, with a minor role played by the interactions between ATP and CH3 TACN which, however, may be important for the build-up of supramolecular assemblies. © 2023 The Royal Society of Chemistry.

One of the key factors, which hampers the application of metallic glasses as structural components, is the localization of deformation in narrow bands of a few tens up to one hundred nanometers thickness, the so-called shear bands. Processes, which occur inside shear bands are of central importance for the question whether a catastrophic failure of the material is unavoidable or can be circumvented or, at least, delayed. Via molecular dynamics simulations, this study addresses one of these processes, namely the local temperature rise due to viscous heat generation. The major contribution to energy dissipation is traced back to the plastic work performed by shear stress during steady deformation. Zones of largest strain contribute the most to this process and coincide with high-temperature domains (hottest spots) inside the sample. Magnitude of temperature rise can reach a few percent of the sample’s glass transition temperature. Consequences of these observations are discussed in the context of the current research in the field. © 2022 by the authors.

The electrical double-layer plays a key role in important interfacial electrochemical processes from catalysis to energy storage and corrosion. Therefore, understanding its structure is crucial for the progress of sustainable technologies. We extract new physico-chemical information on the capacitance and structure of the electrical double-layer of platinum and gold nanoparticles at the molecular level, employing single nanoparticle electrochemistry. The charge storage ability of the solid/liquid interface is larger by one order-of-magnitude than predicted by the traditional mean-field models of the double-layer such as the Gouy–Chapman–Stern model. Performing molecular dynamics simulations, we investigate the possible relationship between the measured high capacitance and adsorption strength of the water adlayer formed at the metal surface. These insights may launch the active tuning of solid–solvent and solvent–solvent interactions as an innovative design strategy to transform energy technologies towards superior performance and sustainability. © 2021 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH

We investigate the effect of low temperature (cryogenic) thermal cycling on dynamics of a generic model glass via molecular dynamics simulations. By calculating mean squared displacements after a varying number of cycles, a pronounced enhancement of dynamics is observed. This rejuvenation effect is visible already after the first cycle and accumulates upon further cycling in an intermittent way. Our data reveal an overall deformation (buckling of the slab-shaped system) modulated by a heterogeneous deformation field due to deep cryogenic thermal cycling. It is shown via strain maps that deformation localizes in the form of shear-bands, which gradually fill the entire sample in a random and intermittent manner, very much similar to the accumulation effect observed in dynamics. While spatial organization of local strain may be connected to the specific geometry, we argue that the heterogeneity of the structure is the main cause behind rejuvenation effects observed in the present study. © 2022 Author(s).

When computing finite-temperature properties of materials with atomistic simulations, nuclear quantum effects are often neglected or approximated at the quasiharmonic level. The inclusion of these effects beyond this level using approaches like the path integral method is often not feasible due to their large computational effort. We discuss and evaluate the performance of a temperature-remapping approach that links the finite-temperature quantum system to its best classical surrogate via a temperature map. This map, which is constructed using the internal energies of classical and quantum harmonic oscillators, is shown to accurately capture the impact of quantum effects on thermodynamic properties at an additional cost that is negligible compared to classical molecular dynamics simulations. Results from this approach show excellent agreement with previously reported path integral Monte Carlo simulation results for diamond cubic carbon and silicon. The approach is also shown to work well for obtaining thermodynamic properties of light metals and for the prediction of the fcc to bcc phase transition in calcium. © 2022 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the "https://creativecommons.org/licenses/by/4.0/"Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Open access publication funded by the Max Planck Society.

In the past two decades, machine learning potentials (MLPs) have reached a level of maturity that now enables applications to large-scale atomistic simulations of a wide range of systems in chemistry, physics, and materials science. Different machine learning algorithms have been used with great success in the construction of these MLPs. In this review, we discuss an important group of MLPs relying on artificial neural networks to establish a mapping from the atomic structure to the potential energy. In spite of this common feature, there are important conceptual differences among MLPs, which concern the dimensionality of the systems, the inclusion of long-range electrostatic interactions, global phenomena like nonlocal charge transfer, and the type of descriptor used to represent the atomic structure, which can be either predefined or learnable. A concise overview is given along with a discussion of the open challenges in the field. © 2022 Annual Reviews Inc.. All rights reserved.

Path sampling approaches have become invaluable tools to explore the mechanisms and dynamics of the so-called rare events that are characterized by transitions between metastable states separated by sizable free energy barriers. Their practical application, in particular to ever more complex molecular systems, is, however, not entirely trivial. Focusing on replica exchange transition interface sampling (RETIS) and forward flux sampling (FFS), we discuss a range of analysis tools that can be used to assess the quality and convergence of such simulations, which is crucial to obtain reliable results. The basic ideas of a step-wise evaluation are exemplified for the study of nucleation in several systems with different complexities, providing a general guide for the critical assessment of RETIS and FFS simulations. © 2022 Author(s).

Compressive stresses in sputter deposited thin films are generally assumed to be caused by forward sputtered (peened) built-in particles and entrapped working gas atoms. While the former are assumed to be predominant, the effect of the latter on interaction dynamics and thin film properties is scarcely clarified (concurrent or causative). The overlay of the ion bombardment induced processes renders an isolation of their contribution impracticable. This issue is addressed by two molecular dynamics case studies considering the sputter deposition of Al thin films in Ar working gas. First, Ar atoms are fully retained. Second, they are artificially neglected, as implanted Ar atoms are assumed to outgas anyhow and not alter the ongoing dynamics significantly. Both case studies share common particle dose impinging Al(001) surfaces. Ion energies from 3 to 300 eV and Al / Ar + flux ratios from 0 to 1 are considered. The surface interactions are simulated by hybrid reactive molecular dynamics/force-biased Monte Carlo simulations and characterized in terms of mass density, Ar concentration, biaxial stress, shear stress, ring statistical connectivity profile, Ar gas porosity, Al vacancy density, and root-mean-squared roughness. Implanted Ar atoms are found to form subnanometer sized eventually outgassing clusters for ion energies exceeding 100 eV. They fundamentally govern a variety of surface processes (e.g., forward sputtering/peening) and surface properties (e.g., compressive stresses) in the considered operating regime. © 2022 Author(s).

The water/fluorite interface is of relevance to diverse industrial, environmental, and medical applications. In this contribution we review some of our recent results on the dynamics of water in contact with the solid calcium fluoride at low pH, where localised charge can develop upon fluorite dissolution. We use ab initio molecular dynamics simulations, including the full electronic structure, to simulate the vibrational energy relaxation and to quantify the heterogeneity of the interfacial water molecules. We find that strongly hydrogen-bonded OH groups display very rapid spectral diffusion and vibrational relaxation; for weakly H-bonded OD groups, the dynamics is instead much slower. Detailed analysis of the simulations reveals the molecular origin of energy transport through the local hydrogen-bond network. In particular, we find that the water molecules in the adsorbed layer, whose orientation is pinned by the localised charge defects, can exchange vibrational energy using just half a solvation shell, thanks to the strong dipole-dipole alignment between H-bond donor and acceptor. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Understanding the acid/base behavior of environmentally relevant organic acids is of key relevance for accurate climate modelling. Here we investigate the effect of pH on the (de)protonation state of pyruvic acid at the air-water interface and in bulk by using the analytical techniques surface-specific vibrational sum frequency generation and attenuated total reflection spectroscopy. To provide a molecular interpretation of the observed behavior, simulations are carried out using a free energy perturbation approach in combination with electronic structure-based molecular dynamics. In both the experimental and theoretical results we observe that the protonated form of pyruvic acid is preferred at the air-water interface. The increased proton affinity is the result of the specific microsolvation at the interface. © 2022 The Royal Society of Chemistry

Liquid-infused surfaces are based upon the infusion of a liquid phase into a porous solid material to induce slippery and repellent character. In this context, porous SiOx plasma polymer films represent a relevant candidate for a robust nanoporous carrier layer. Intermittent low-pressure plasma etching of O2/hexamethyldisiloxane-derived coatings is investigated to enhance the intrinsic porosity inherent to residual hydrocarbons in the silica matrix. Simulations of the resulting Si–O ring network structure using reactive molecular dynamics indicate formation of interconnected voids with Si–OH functionalized pore walls allowing water penetration with almost Fickian diffusive behavior. The corresponding porosity of up to 18%, well agreeing with simulations, Fourier-transform infrared spectroscopy, and ellipsometry measurements, was found to be suitable for the liquid infusion of polyethylene glycol molecules into about 80 nm thick SiOx films providing ongoing lubricating properties, thus revealing their suitability as liquid-infused surfaces. © 2022 The Authors. Plasma Processes and Polymers published by Wiley-VCH GmbH.

Second nearest neighbor modified embedded atom method (2NN-MEAM) interatomic potentials are developed for the Ni, Re, and Ni-Re binaries. To construct the potentials, density functional theory (DFT) calculations have been employed to calculate fundamental physical properties that play a dominant role in fracture. The potentials are validated to accurately reproduce material properties that correlate with material's fracture behavior. The thus constructed potentials were applied to perform large scale simulations of mode I fracture in Ni and Ni-Re binaries with low Re content. Substitutional Re did not alter the ductile nature of crack propagation, though it resulted in a monotonous increase of the critical stress intensity factor with Re content. © 2021 The Author(s). Published by IOP Publishing Ltd.

The lattice of the flexible Metal–Organic Framework (MOF) MIL-88B(Fe)-Cl is strongly modified when it is subjected to methanol vapor, increasing its volume by more than 130 %. We use a newly developed interaction model belonging to the extended MOF-FF family to perform classical Molecular Dynamics (MD) simulations of this MOF with varying amounts of methanol guest molecules. This work focuses on the evolving intermolecular structure of the counterions and guest molecules when their number is increased from 1 to 30 per cavity. Two mobile Cl−-counterions are, on the average, present in each lattice cavity to neutralize the framework charges. At low loadings (in the closed (or semi-closed) systems), the methanol molecules aggregate around these ions, which are themselves pegged, at the time scale of the simulation, to the Fe3-centers of the MOF. At loadings just below the transition, such methanol aggregates may link two counterions on opposite Fe3-centers, thus preventing the MOF from opening unless more methanol is added. In all closed systems, the methanol self-diffusion is almost two orders of magnitude lower than in the bulk liquid. Once the MOF opens, i.e., at loadings higher than about 12 to 13 methanol molecules per cavity, structural features typical of liquid methanol become more and more apparent. However, the evolution is not monotonous, there is a transitional region up to about 22 molecules par cavity. Increasing the loading further, all features more and more resemble the ones of bulk liquid methanol. © 2022 Elsevier B.V.

Coupled cluster theory is a general and systematic electronic structure method, but in particular the highly accurate "gold standard"coupled cluster singles, doubles and perturbative triples, CCSD(T), can only be applied to small systems. To overcome this limitation, we introduce a framework to transfer CCSD(T) accuracy of finite molecular clusters to extended condensed phase systems using a high-dimensional neural network potential. This approach, which is automated, allows one to perform high-quality coupled cluster molecular dynamics, CCMD, as we demonstrate for liquid water including nuclear quantum effects. The machine learning strategy is very efficient, generic, can be systematically improved, and is applicable to a variety of complex systems. © 2022 American Physical Society.

The Gibbs free energy of grain boundaries (GBs) in Al bicrystals has been investigated by Molecular Dynamics (MD) simulations. In our novel approach, one grain is fully embedded in a large matrix grain with fixed misorientation. Hence all inclinations are considered simultaneously since the boundary covers the full orientation subspace. A synthetical driving force is employed to counteract the shrinkage of the embedded grain by the capillary forces. Hence, the number of atoms of the embedded grain is kept constant, but its shape adjusts itself at elevated temperatures in order to minimize the total GB energy. The quasi-equilibrium shapes are used to derive the GB energy γ(n) as functions of the GB plane normal n. For GBs with the misorientations Σ5〈001〉 and Σ7〈111〉, analytical functions were derived and validated in a mesoscopic front-tracking simulation: the latter simulations recovered the grain shapes observed in MD simulations. For the Σ5〈001〉 misorientation it is shown that the anisotropy of γ(n) varies quite strongly with temperature. For a Σ9〈110〉 misorientation, the derived numerical energy function was found to be rather complex, showing pronounced energy minima for mixed tilt/twist GBs parallel to 111 crystal planes. © 2021 Elsevier B.V.

Controlling the transport of thermal energy is key to most applications of metal–organic frameworks (MOFs). Analyzing the evolution of the effective local temperature, the interfaces between the metal nodes and the organic linkers are identified as the primary bottlenecks for heat conduction. Consequently, changing the bonding strength at that node–linker interface and the mass of the metal atoms can be exploited to tune the thermal conductivity. This insight is generated employing molecular dynamics simulations in conjunction with advanced, ab initio parameterized force fields. The focus of the present study is on MOF-5 as a prototypical example of an isoreticular MOF. However, the key findings prevail for different node structures and node–linker bonding chemistries. The presented results lay the foundation for developing detailed structure-to-property relationships for thermal transport in MOFs with the goal of devising strategies for the application-specific optimization of heat conduction. © 2020 The Authors. Advanced Theory and Simulations published by Wiley-VCH GmbH

Atomistic mass and charge distribution at electrified interfaces play a key role in electrochemical phenomena of huge technological relevance for energy production and conversion. However, in spite of its importance, the structure of the double layer at the nanoscale is still to a large extent unknown, even for Pt-water, the most fundamental electrochemical interface. Using a new, general ab initio methodology to model charged electrodes, we simulate the atomistic structure of the Pt-water double layer and its response to an applied potential, in realistic solution conditions. We evaluate the interface capacitance and the absolute electrode potential for three states of charge of the electrode. We reveal that electrode polarisation induces interfacial electronic charge spillover and oscillation, and changes the surface coverage of the first adsorbed water layer. Since the molecules in this layer are all found to be equally charged, the interface dipole is strongly affected by such change of coverage, while water reorientation becomes relevant only from the second water layer. Our findings will be essential to develop highly realistic models for catalytic processes at the Pt-water interface. © 2021

Nd2Fe14B-type materials exhibit the highest energy product around room temperature and hence dominate the high-performance permanent magnet market. Intensive research efforts aim at alternative material systems containing less critical elements with similar or better magnetic properties. Nd- and Sm-based compounds with a ThMn12-type structure exhibit intrinsic properties comparable or even superior to Nd2Fe14B. However, it has not been possible to achieve technically relevant coercivity and remanent magnetization in ThMn12-based bulk sintered magnets. Using SmFe11Ti as a prototypical representative, we demonstrate that one important reason for the poor performance is the formation of twins inside micro-crystalline grains. The nature of the twins in SmFe11Ti was investigated in twinned “single crystals” and both bulk and thin film poly-crystalline samples, using advanced electron microscopy and atom probe tomography as well as simulations and compared with benchmark Nd2Fe14B. Both micro-twins and nano-twins show a twin orientation of 57±2° and an enrichment in Sm, which could affect domain wall motion in this material. Micromagnetic simulations indicate that twins act as nucleation centers, representing the magnetically weakest link in the microstructure. The relation between twin formation energies and geometrical features are briefly discussed using molecular dynamic simulations. © 2021

We present an automatized workflow which, starting from molecular dynamics simulations, identifies reaction events, filters them, and prepares them for accurate quantum chemical calculations using, for example, Density Functional Theory (DFT) or Coupled Cluster methods. The capabilities of the automatized workflow are demonstrated by the example of simulations for the combustion of some polycyclic aromatic hydrocarbons (PAHs). It is shown how key elementary reaction candidates are filtered out of a much larger set of redundant reactions and refined further. The molecular species in question are optimized using DFT and reaction energies, barrier heights, and reaction rates are calculated. The setup is general enough to include at this stage configurational sampling, which can be exploited in the future. Using the introduced machinery, we investigate how the observed reaction types depend on the gas atmosphere used in the molecular dynamics simulation. For the re-optimization on the DFT level, we show how the additional information needed to switch from reactive force-field to electronic structure calculations can be filled in and study how well ReaxFF and DFT agree with each other and shine light on the perspective of using more accurate semi-empirical methods in the MD simulation. © 2021 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.

Unraveling the atomistic and the electronic structure of solid-liquid interfaces is the key to the design of new materials for many important applications, from heterogeneous catalysis to battery technology. Density functional theory (DFT) calculations can, in principle, provide a reliable description of such interfaces, but the high computational costs severely restrict the accessible time and length scales. Here, we report machine learning-driven simulations of various interfaces between water and lithium manganese oxide (LixMn2O4), an important electrode material in lithium ion batteries and a catalyst for the oxygen evolution reaction. We employ a high-dimensional neural network potential to compute the energies and forces several orders of magnitude faster than DFT without loss in accuracy. In addition, a high-dimensional neural network for spin prediction is utilized to analyze the electronic structure of the manganese ions. Combining these methods, a series of interfaces is investigated by large-scale molecular dynamics. The simulations allow us to gain insights into a variety of properties, such as the dissociation of water molecules, proton transfer processes, and hydrogen bonds, as well as the geometric and electronic structure of the solid surfaces, including the manganese oxidation state distribution, Jahn-Teller distortions, and electron hopping. © 2021 Author(s).

Flexible metal–organic frameworks (MOFs) show large structural flexibility as a function of temperature or (gas)pressure variation, a fascinating property of high technological and scientific relevance. The targeted design of flexible MOFs demands control over the macroscopic thermodynamics as determined by microscopic chemical interactions and remains an open challenge. Herein we apply high-pressure powder X-ray diffraction and molecular dynamics simulations to gain insight into the microscopic chemical factors that determine the high-pressure macroscopic thermodynamics of two flexible pillared-layer MOFs. For the first time we identify configurational entropy that originates from side-chain modifications of the linker as the key factor determining the thermodynamics in a flexible MOF. The study shows that configurational entropy is an important yet largely overlooked parameter, providing an intriguing perspective of how to chemically access the underlying free energy landscape in MOFs. © 2020 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH

Volume changes are observed in the metal-organic frameworks (MOFs) of the MIL-88 family when they are exposed to certain solvents. We investigate here, at the atomic level, the swelling behavior of MIL-88B absorbing strongly interacting guest molecules, methanol, for which the largest changes are found. The MOF is positively charged and possesses open metal sites at the trimetallic inorganic building units (M3O), with which the counterions and guests coordinate. We develop an extended MOF-FF-type interaction model and perform the first molecular dynamics (MD) simulations to describe the structural changes of the flexible MIL-88B(Fe)-Cl upon insertion of methanol. The newly developed interaction model according to the MOF-FF scheme consists of (I) the intra-MOF interactions, (II) a fully MOF-FF-compatible model for the methanol and the solvated Cl- ion, which was recently published, and (III) specific new terms developed for the interactions between a trimetallic building unit (Fe3O) connected with six benzoate rings and these species. We report the free energy versus volume profiles as a function of loading and temperature, which are matched with the evolution of the unit cell volume versus the methanol loading profile. We discuss radial pair distribution functions (rdf) and some three-dimensional distributions of the counterions around Fe3O. We find that the pore opening is accompanied by characteristic structural changes in the arrangements of the counterions near the central Fe3 units and also of the solvent coordinating these counterions: this illustrates the role of the solvated counterions in the swelling process. © 2021 American Chemical Society. All rights reserved.

The use of biomolecules as capping and reducing agents in the synthesis of metallic nanoparticles constitutes a promising framework to achieve desired functional properties with minimal toxicity. The system's complexity and the large number of variables involved represent a challenge for theoretical and experimental investigations aiming at devising precise synthesis protocols. In this work, we use L-asparagine (Asn), an amino acid building block of large biomolecular systems, to synthesise gold nanoparticles (AuNPs) in aqueous solution at controlled pH. The use of Asn offers a primary system that allows us to understand the role of biomolecules in synthesising metallic nanoparticles. Our results indicate that AuNPs synthesised in acidic (pH 6) and basic (pH 9) environments exhibit somewhat different morphologies.We investigate these AuNPs via Raman scattering experiments and classical molecular dynamics simulations of zwitterionic and anionic Asn states adsorbing on (111)-, (100)-, (110)-, and (311)-oriented gold surfaces. A combined analysis suggests that the underlying mechanism controlling AuNPs geometry correlates with amine's preferential adsorption over ammonium groups, enhanced upon increasing pH. Our simulations reveal that Asn (both zwitterionic and anionic) adsorption on gold (111) is essentially different from adsorption on more open surfaces. Water molecules strongly interact with the gold face-centred-cubic lattice and create traps, on the more open surfaces, that prevent the Asn from diffusing. These results indicate that pH is a relevant parameter in green-synthesis protocols with the capability to control the nanoparticle's geometry, and pave the way to computational studies exploring the effect of water monolayers on the adsorption of small molecules on wet gold surfaces. © 2021 The Author(s).

Small additive molecules often enhance structural relaxation in polymers. We explore this effect in a thermoplastic shape memory polymer via molecular dynamics simulations. The additiveto-monomer size ratio is shown to play a key role here. While the effect of additive-concentration on the rate of shape recovery is found to be monotonic in the investigated range, a non-monotonic dependence on the size-ratio emerges at temperatures close to the glass transition. This work thus identifies the additives’ size to be a qualitatively novel parameter for controlling the recovery process in polymer-based shape memory materials. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

One of the most investigated properties of porous crystalline metal-organic frameworks (MOFs) is their potential flexibility to undergo large changes in unit cell size upon guest adsorption or other stimuli, referred to as “breathing”. Computationally, such phase transitions are usually investigated using periodic boundary conditions, where the system’s volume can be controlled directly. However, we have recently shown that important aspects like the formation of a moving interface between the open and the closed pore form or the free energy barrier of the first-order phase transition and its size effects can best be investigated using non-periodic nanocrystallite (NC) models [Keupp et al. (Adv. Theory Simul., 2019, 2, 1900117)]. In this case, the application of pressure is not straightforward, and a distance constraint was used to mimic a mechanical strain enforcing the reaction coordinate. In contrast to this prior work, a mediating particle bath is used here to exert an isotropic hydrostatic pressure on the MOF nanocrystallites. The approach is inspired by the mercury nanoporosimetry used to compress flexible MOF powders. For such a mediating medium, parameters are presented that require a reasonable additional numerical effort and avoid unwanted diffusion of bath particles into the MOF pores. As a proof-of-concept, NCs of pillared-layer MOFs with different linkers and sizes are studied concerning their response to external pressure exerted by the bath. By this approach, an isotropic pressure on the NC can be applied in analogy to corresponding periodic simulations, without any bias for a specific mechanism. This allows a more realistic investigation of the breathing phase transformation of a MOF NC and further bridges the gap between experiment and simulation. © Copyright © 2021 Schaper, Keupp and Schmid.

The interface method is a well established approach for predicting melting points of materials using interatomic potentials. However, applying the interface method is tedious and involves significant human intervention. The whole procedure involves several successive tasks: estimate a rough melting point, set up the interface structure, run molecular dynamic calculations and analyze the data. Loop calculations are necessary if the predicted melting point is different from the estimated one by more than a certain convergence criterion, or if full melting/solidification occurs. In this case monitoring the solid–liquid phase transition in the interface structure becomes critical. As different initial random seeds for the molecular dynamic simulations within the interface method induce slightly different melting points, a few ten or hundred interface method calculations with different random seeds are necessary for performing a statistical analysis on these melting points. Considering all these technical details, the work load for manually executing and combining the various involved scripts and programs quickly becomes prohibitive. To simplify and automatize the whole procedure, we have implemented the interface method into pyiron (http://pyiron.org). Our fully automatized procedure allows to efficiently and precisely predict melting points of stable unaries represented by arbitrary potentials with only two user-specified parameters (interatomic potential file and element). For metastable or dynamically unstable unary phases, the crystal structure needs to be provided as an additional parameter. We have applied our automatized approach on fcc Al, Ni, dynamically unstable bcc Ti and hcp Mg and employed a large set of available interatomic potentials. Melting points for classical interatomic potentials of these metals have been obtained with a numerical precision well below 1 K. © 2020 The Authors

Grain boundaries (GBs) in metals usually increase electrical resistivity due to their distinct atomic arrangement compared to the grain interior. While the GB structure has a crucial influence on the electrical properties, its relationship with resistivity is poorly understood. Here, we perform a systematic study on the resistivity-structure relationship in Cu tilt GBs, employing high-resolution in situ electrical measurements coupled with atomic structure analysis of the GBs. Excess volume and energies of selected GBs are calculated using molecular dynamics simulations. We find a consistent relation between the coincidence site lattice (CSL) type of the GB and its resistivity. The most resistive GBs are in the high range of low-angle GBs (14°-18°) with twice the resistivity of high angle tilt GBs, due to the high dislocation density and corresponding strain fields. Regarding the atomistic structure, GB resistivity approximately correlates with the GB excess volume. Moreover, we show that GB curvature increases resistivity by ∼80%, while phase variations and defects within the same CSL type do not considerably change it. © 2021 The Authors. Published by American Chemical Society.

Elemental antimony has been recently proposed as a promising material for phase change memories with improved performances with respect to the most used ternary chalcogenide alloys. The compositional simplification prevents reliability problems due to demixing of the alloy during memory operation. This is made possible by the dramatic stabilization of the amorphous phase once Sb is confined in an ultrathin film 3-5 nm thick. In this work, we shed light on the microscopic origin of this effect by means of large scale molecular dynamics simulations based on an interatomic potential generated with a machine learning technique. The simulations suggest that the dramatic reduction of the crystal growth velocity in the film with respect to the bulk is due to the effect of nanoconfinement on the fast β relaxation dynamics while the slow α relaxation is essentially unaffected. © The Royal Society of Chemistry.

It has been shown that a weak shear can induce crystallisation in a disordered, glassy state. In this study, we use molecular dynamics simulations in order to investigate the out-of-equilibrium properties of [BMIM][BF4] confined between metal slabs. In particular, we want to understand the extent to which the shear flow modifies the interfacial properties. In particular, the questions we address here are (i) is the shear able to promote the crystalline phase in [BMIM][BF4]? (ii) Can, as a consequence of shear flow, a solid-like layer develop at the interface with a metallic surface? (iii) What are the tribological properties of nanoconfined [BMIM][BF4]? We find that the system behaves quite differently from the ideal linear Couette flow. Indeed, the portion of fluid closer to the shearing slabs behaves as a disordered, solid-like layer, which, under the investigated conditions extends to a few nanometres. The linear velocity regime is only recovered in the central region of the ionic liquid slab. The formation of such a solid-like glassy rather than crystalline layer is in agreement with recent mechanical impedance measurements performed on nano-confined ionic liquids. © the Owner Societies 2021.

The double layer at the solid/electrolyte interface is a key concept in electrochemistry. Here, we present an experimental study combined with simulations, which provides a molecular picture of the double-layer formation under applied voltage. By THz spectroscopy we are able to follow the stripping away of the cation/anion hydration shells for an NaCl electrolyte at the Au surface when decreasing/increasing the bias potential. While Na+ is attracted toward the electrode at the smallest applied negative potentials, stripping of the Cl2 hydration shell is observed only at higher potential values. These phenomena are directly measured by THz spectroscopy with ultrabright synchrotron light as a source and rationalized by accompanying molecular dynamics simulations and electronic-structure calculations. © 2021 National Academy of Sciences. All rights reserved.

We introduce a novel approach to sample the canonical ensemble at constant temperature and applied electric potential. Our approach can be straightforwardly implemented into any density-functional theory code. Using thermopotentiostat molecular dynamics simulations allows us to compute the dielectric constant of nanoconfined water without any assumptions for the dielectric volume. Compared to the commonly used approach of calculating dielectric properties from polarization fluctuations, our thermopotentiostat technique reduces the required computational time by 2 orders of magnitude. © 2021 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the "https://creativecommons.org/licenses/by/4.0/"Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Density functional theory molecular dynamics simulations of H-covered Pt(111)-H2O interfaces reveal that, in contrast to common understanding, H2O coadsorption has a significant impact on the electrode potential of and plays a major role in determining the stability of H adsorbates under electrochemical conditions. Based on these insights, we explain the origin behind the experimentally observed upper limit of H coverage well below one monolayer and derive a chemically intuitive model for metal-water bonding that explains an unexpectedly large interaction between coadsorbed water and adsorbates. © 2021 authors.

Deformation-induced characteristics of surface layer strongly rely on loading condition-related operating deformation modes. In the current study we reveal the mechanisms governing machined surface formation of hard brittle monocrystalline 3C–SiC in ultrasonic elliptical vibration-assisted diamond cutting by molecular dynamics simulations. Simulation results show different deformation modes including phase transformation, dislocation activity, and crack nucleation and propagation, as well as their correlations with surface integrity in terms of machined surface morphology and subsurface damage. In particular, molecular dynamics simulations of ordinary cutting are also carried out, which demonstrate the effectiveness of applying ultrasonic vibration of cutting tool in decreasing machining force and suppressing crack events, i.e., promoting ductile-mode cutting for achieving high surface integrity. The physical mechanism governing the machining differences between the two machining processes are also revealed. Furthermore, the effect of cutting depth on machined surface integrity under vibration-assisted cutting and ordinary cutting is addressed. © 2020 Elsevier Ltd and Techna Group S.r.l.

We elucidate the crucial role of the cetyl trimethylammonium bromide (CTAB) surfactant in the anisotropic growth mechanism of gold nano-bipyramids, nano-objects with remarkable optical properties and high tunability. Atomistic molecular dynamics simulations predict different surface coverages of the CTAB (positively charged) heads and their (bromide) counterions as function of the gold exposed surfaces. High concentration of CTAB surfactant promotes formation of gold nanograins in solution that work as precursors for the smooth anisotropic growth of more elongated nano-bipyramidal objects. Nanobipyramids feature higher index facets with respect to nanorods, allowing higher CTAB coverages that stabilize their formation and leading to narrower inter-micelles channels that smooth down their anisotropic growth. Absorption spectroscopy and scanning electron microscopy confirmed the formation of nanograins and demonstrated the importance of surfactant concentration on driving the growth towards nano-bipyramids rather than nanorods. The outcome explains the formation of the monodisperse bipyramidal nano-objects, the origin of their controlled shapes and sizes along with their remarkable stability. © The Royal Society of Chemistry.

Variable charge models (e.g., electronegativity equalization method (EEM), charge equilibration (QEq), electrostatic plus (ES+)) used in reactive molecular dynamics simulations often inherently impose a global charge transfer between atoms (approximating each system as an ideal metal). Consequently, most surface processes (e.g., adsorption, desorption, deposition, sputtering) are affected, potentially causing dubious dynamics. This issue has been addressed by certain split charge variants (i.e., split charge equilibration (SQE), redoxSQE) through a distance-dependent bond hardness, by the atomic charge ACKS2 and QTPIE models, which are based on the Kohn-Sham density functional theory, as well as by an electronegativity screening extension to the QEq model (approximating each system as an ideal insulator). In a brief review of the QEq and the QTPIE model, their applicability for studying surface interactions is assessed in this work. Following this evaluation, a revised generalization of the QEq and QTPIE models is proposed and formulated, called the charge-transfer equilibration model or in short the QTE model. This method is based on the equilibration of charge-transfer variables, which locally constrain the split charge transfer per unit time (i.e., due to overlapping orbitals) without any kind of bond hardness specification. Furthermore, a formalism relying solely on atomic charges is obtained by a respective transformation, employing an extended Lagrangian method. We moreover propose a mirror boundary condition and its implementation to accelerate surface investigations. The models proposed in this work facilitate reactive molecular dynamics simulations, which describe various materials and surface phenomena appropriately. © 2021 The Authors. Published by American Chemical Society.

An active learning approach to train machine-learning interatomic potentials (moment tensor potentials) for multicomponent alloys to ab initio data is presented. Employing this approach, the disordered body-centered cubic (bcc) TiZrHfTax system with varying Ta concentration is investigated via molecular dynamics simulations. Our results show a strong interplay between elastic properties and the structural ω phase stability, strongly affecting the mechanical properties. Based on these insights we systematically screen composition space for regimes where elastic constants show little or no temperature dependence (elinvar effect). © 2021 American Physical Society.

Understanding the orientation-dependent deformation behavior of NiTi shape-memory alloys at small length scales is of importance for designing nano- and micro-electromechanical systems. However, a complete understanding of the orientation- and size-dependent competition between the various modes of slip, deformation twinning, and martensitic transformation in NiTi shape-memory alloys is still lacking, especially in micron-scale specimens. In the present study, we perform micro-compression tests on [001]- and [112]-oriented micro-pillars of a solutionized Ti-49.9at.% Ni alloy. Post-mortem TEM analysis of the deformed pillars reveal that the operating plastic deformation modes are {011}<100> slip and {114}<221¯> deformation twinning, which compete with the martensitic transformation, depending on the crystal orientation. Furthermore, in both experiments and molecular dynamics simulations, we consistently find residual B19′ martensite in a herringbone microstructure composed of finely spaced (001)B19′ compound twins instead of the generally assumed [011]B19′ type II twins common in bulk samples, suggesting that the operative martensitic transformation mode may be size-dependent. Schmid factors in compression are calculated for all commonly reported slip, deformation twinning, and martensitic transformation modes as a function of crystallographic orientation, which rationalize the orientation-dependent competition between these deformation modes. © 2021 Acta Materialia Inc.

The prototypical pillared layer MOFs, formed by a square lattice of paddle-wheel units and connected by dinitrogen pillars, can undergo a breathing phase transition by a "wine-rack"type motion of the square lattice. We studied this behavior, which is not yet fully understood, using an accurate first principles parameterized force field (MOF-FF) for larger nanocrystallites on the example of Zn2(bdc)2(dabco) [bdc: benzenedicarboxylate, dabco: (1,4-diazabicyclo[2.2.2]octane)], and found clear indications for an interface between a closed and an open pore phase traveling through the system during the phase transformation [J. Keupp and R. Schmid, Adv. Theory Simul., 2019, 2, 1900117]. In conventional simulations in small supercells this mechanism is prevented by periodic boundary conditions (PBCs), enforcing a synchronous transformation of the entire crystal. Here, we extend this investigation to pillared layer MOFs with flexible side-chains, attached to the linker. Such functionalized (fu-)MOFs are experimentally known to have different properties with the side-chains acting as fixed guest molecules. First, in order to extend the parameterization for such flexible groups, a new parameterization strategy for MOF-FF had to be developed, using a multi-structure force based fit method. The resulting parameterization for a library of fu-MOFs is then validated with respect to a set of reference systems and shows very good accuracy. In the second step, a series of fu-MOFs with increasing side-chain length is studied with respect to the influence of the side-chains on the breathing behavior. For small supercells in PBCs a systematic trend of the closed pore volume with the chain length is observed. However, for a nanocrystallite model a distinct interface between a closed and an open pore phase is visible only for the short chain length, whereas for longer chains the interface broadens and a nearly concerted transformation is observed. Only by molecular dynamics simulations using accurate force fields can such complex phenomena can be studied on a molecular level. © 2021 The Royal Society of Chemistry.

Differential scanning calorimetry measurements on different bulk metallic glasses show no measurable rejuvenation upon deeply cooled (cryogenic) thermal cycling. This applies both to as-quenched and well-annealed samples. Extensive molecular dynamics simulations of a generic model glass former corroborate these observations. We disentangle the effects of aging from those of thermal treatment and show that aging is slowed down but not stopped - neither reversed - during thermal cycling. These observations are corroborated further by a survey of energy distribution, which continues narrowing, albeit with a smaller rate. © 2021 authors.

Nanoparticles have become increasingly interesting for a wide range of applications because in principle it is possible to tailor their properties by controlling size, shape, and composition. One of these applications is heterogeneous catalysis, and a fundamental understanding of the structural details of the nanoparticles is essential for any knowledge-based improvement of reactivity and selectivity. In this work, we investigate the atomic structure of brass nanoparticles containing up to 5000 atoms as a typical example for a binary alloy consisting of Cu and Zn. As systems of this size are too large for electronic structure calculations, in our simulations, we use a recently parameterized machine learning potential providing close to density functional theory accuracy. This potential is employed for a structural characterization as a function of chemical composition by various types of simulations such as Monte Carlo in the semigrand canonical ensemble and simulated annealing molecular dynamics. Our analysis reveals that the distribution of both elements in the nanoparticles is inhomogeneous, and zinc accumulates in the outermost layer, while the first subsurface layer shows an enrichment of copper. Only for high zinc concentrations, alloying can be found in the interior of the nanoparticles, and regular patterns corresponding to crystalline bulk phases of α-brass can then be observed. The surfaces of the investigated clusters exhibit well-ordered single-crystal facets, which can give rise to grain boundaries inside the clusters. The melting temperature of the nanoparticles is found to decrease with increasing zinc-atom fraction, a trend which is well known also for the bulk phase diagram of brass. © 2021 The Authors. Published by American Chemical Society.

We use molecular dynamics (MD) simulation with numerical characterisation and statistical analysis to study the mechanisms of damage evolution and p-type doping efficiency by aluminum (Al) ion implantation into 3C silicon carbide (SiC) with subsequent annealing. By incorporating the electronic stopping power for implantation, a more accurate description of the atomic-scale mechanisms of damage evolution and distribution in SiC can be obtained. The simulation results show a novel observation that the recrystallization process occurs in the region below the subsurface layer, and develops from amorphous-crystalline interface to the damage center region, which is a new insight into previously published studies. During surface recrystallization, significant compressive stress concentration occurs, and more structural phase transition atoms and dislocations formed at the damage-rich-crystalline interface. Another point of interest is that for low-dose implantation, more implantation-induced defects hamper the doping efficiency. Correspondingly, the correlation between lattice damage and doping efficiency becomes weaker as the implant dose increases under the same annealing conditions. Our simulation also predicts that annealing after high temperature (HT) implantation is more likely to lead to the formation of carbon vacancies (VC). © The Royal Society of Chemistry 2021.

Alkaline electrolyte solutions are important components in rechargeable batteries and alkaline fuel cells. As the ionic conductivity is thought to be a limiting factor in the performance of these devices, which are often operated at elevated temperatures, its temperature dependence is of significant interest. Here we use NaOH as a prototypical example of alkaline electrolytes, and for this system we have carried out reactive molecular dynamics simulations with an experimentally verified high-dimensional neural network potential derived from density-functional theory calculations. It is found that in concentrated NaOH solutions elevated temperatures enhance both the contributions of proton transfer to the ionic conductivity and deviations from the Nernst-Einstein relation. These findings are expected to be of practical relevance for electrochemical devices based on alkaline electrolyte solutions. This journal is © the Owner Societies.

Phase equilibria of fluid substances and their mixtures are important in numerous scientific as well as industrial applications and are, therefore, a major focus of thermophysical property research. For the development and improvement of thermophysical property models, reliable experimental data are crucial. However, measurements of thermophysical properties in the vicinity of the dew line can be substantially distorted by surface phenomena such as adsorption and capillary condensation on the quasi nonporous metal surfaces of the experimental apparatuses. To support the qualitative understanding of these phenomena on an atomistic level and to estimate their impact on experiments, we performed classical molecular dynamics (MD) simulations. As a first proof-of-concept investigation, we focused on pure CO2 on an idealized face-centered cubic (fcc) {111} gold surface. The results, in the form of an adsorption isotherm at T = 283.15 K, are compared to sorption measurements using a specially designed gold sinker incorporated in an optimized gravimetric sorption analyzer. This first comparison between atomistic MD simulations and gravimetric experiments helps in assessing the applicability of our simulation technique and paves the way for a deeper understanding of the relevant surface phenomena occurring in our apparatus. © 2020 American Chemical Society.

Lithium ion batteries often contain transition metal oxides such as LixMn2O4 (0 ≤ x ≤ 2). Depending on the Li content, different ratios of MnIII to MnIV ions are present. In combination with electron hopping, the Jahn-Teller distortions of the MnIIIO6 octahedra can give rise to complex phenomena such as structural transitions and conductance. While for small model systems oxidation and spin states can be determined using density functional theory (DFT), the investigation of dynamical phenomena by DFT is too demanding. Previously, we have shown that a high-dimensional neural network potential can extend molecular dynamics (MD) simulations of LixMn2O4 to nanosecond time scales, but these simulations did not provide information about the electronic structure. Here, we extend the use of neural networks to the prediction of atomic oxidation and spin states. The resulting high-dimensional neural network is able to predict the spins of the Mn ions with an error of only 0.03 We find that the Mn eg electrons are correctly conserved and that the number of Jahn-Teller distorted MnIIIO6 octahedra is predicted precisely for different Li loadings. A charge ordering transition is observed between 280 K and 300 K, which matches resistivity measurements. Moreover, the activation energy of the electron hopping conduction above the phase transition is predicted to be 0.18 eV, deviating only 0.02 eV from experiment. This work demonstrates that machine learning is able to provide an accurate representation of both the geometric and the electronic structure dynamics of LixMn2O4 on time and length scales that are not accessible by ab initio MD. © 2020 Author(s).

Water permeation between stacked layers of hBN sheets forming 2D nanochannels is investigated using large-scale ab initio-quality molecular dynamics simulations. A high-dimensional neural network potential trained on density-functional theory calculations is employed. We simulate water in van der Waals nanocapillaries and study the impact of nanometric confinement on the structure and dynamics of water using both equilibrium and nonequilibrium methods. At an interlayer distance of 10.2 Å confinement induces a first-order phase transition resulting in a well-defined AA-stacked bilayer of hexagonal ice. In contrast, for h < 9 Å, the 2D water monolayer consists of a mixture of different locally ordered patterns of squares, pentagons, and hexagons. We found a significant change in the transport properties of confined water, particularly for monolayer water where the water-solid friction coefficient decreases to half and the diffusion coefficient increases by a factor of 4 as compared to bulk water. Accordingly, the slip-velocity is found to increase under confinement and we found that the overall permeation is dominated by monolayer water adjacent to the hBN membranes at extreme confinements. We conclude that monolayer water in addition to bilayer ice has a major contribution to water transport through 2D nanochannels. Copyright © 2020 American Chemical Society.

The presence of facets and line junctions connecting facets on grain boundaries (GBs) has a strong impact on the properties of structural, functional, and optoelectronic materials: They govern the mobility of interfaces, the segregation of impurities, as well the electronic properties. In the present paper, we employ density-functional theory and modified embedded atom method calculations to systematically investigate the energetics and thermodynamic stability of these defects. As a prototype system, we consider ς3 tilt GBs in Si. By analyzing the energetics of different faceted GBs, we derive a diagram that describes and predicts the reconstruction of these extended defects as a function of facet length and boundary inclination angle. The phase diagram sheds light upon the fundamental mechanisms causing GB faceting phenomena. It demonstrates that the properties of faceting are not determined solely by anisotropic GB energies but by a complex interplay between geometry and microstructure, boundary energies as well as long-range strain interactions. © 2020 authors. Published by the American Physical Society. Open access publication funded by the Max Planck Society.

Interatomic potentials are essential for studying fundamental mechanisms of deformation and failure in metals and alloys because the relevant defects (dislocations, cracks, etc.) are far above the scales accessible to first-principles studies. Existing potentials for non-fcc metals and nearly all alloys are, however, not sufficiently quantitative for many crucial phenomena. Here machine learning in the Behler-Parrinello neural-network framework is used to create a broadly applicable potential for pure hcp magnesium (Mg). Lightweight Mg and its alloys are technologically important while presenting a diverse range of slip systems and crystal surfaces relevant to both plasticity and fracture that present a significant challenge for any potential. The machine learning potential is trained on first-principles density-functional theory (DFT) computable metallurgically relevant properties and is then shown to well predict metallurgically crucial dislocation and crack structures and competing phenomena. Extensive comparisons to an existing very good modified embedded atom method potential are made. These results demonstrate that a single machine learning potential can represent the wide scope of phenomena required for metallurgical studies. The DFT database is openly available for use in any other machine learning method. The method is naturally extendable to alloys, which are necessary for engineering applications but where ductility and fracture are controlled by complex atomic-scale mechanisms that are not well predicted by existing potentials. © 2020 American Physical Society.

The peculiar properties of ionic liquids in confinement have not only become essential for energy storage, catalysis and tribology, but still pose fundamental questions. Recently, an anomalous liquid-solid phase transition has been observed in atomic force microscopy experiments for 1-butyl-3-methylimidazolium tetrafluoroborate ([BMIM][BF4]), the transition being more pronounced for metallic surfaces. Image charges have been suggested as the key element driving the anomalous freezing. Using atomistic molecular dynamics simulations, we investigate the impact of image charges on structure, dynamics and thermodynamics of [BMIM][BF4] confined between gold electrodes. Our results not only unveil a minor role played by the metal polarisation, but also provide a novel description of the interfacial layer. Although no diffuse layer can be defined in terms of the electrostatic potential, long range effects are clearly visible in the dynamical properties up to 10 nanometers away from the surface, and are expected to influence viscous forces in the experiments. This journal is © the Owner Societies.

The theory of grain boundary (the interface between crystallites, GB) structure has a long history1 and the concept of GBs undergoing phase transformations was proposed 50 years ago2,3. The underlying assumption was that multiple stable and metastable states exist for different GB orientations4–6. The terminology ‘complexion’ was recently proposed to distinguish between interfacial states that differ in any equilibrium thermodynamic property7. Different types of complexion and transitions between complexions have been characterized, mostly in binary or multicomponent systems8–19. Simulations have provided insight into the phase behaviour of interfaces and shown that GB transitions can occur in many material systems20–24. However, the direct experimental observation and transformation kinetics of GBs in an elemental metal have remained elusive. Here we demonstrate atomic-scale GB phase coexistence and transformations at symmetric and asymmetric [11 1 ¯] tilt GBs in elemental copper. Atomic-resolution imaging reveals the coexistence of two different structures at Σ19b GBs (where Σ19 is the density of coincident sites and b is a GB variant), in agreement with evolutionary GB structure search and clustering analysis21,25,26. We also use finite-temperature molecular dynamics simulations to explore the coexistence and transformation kinetics of these GB phases. Our results demonstrate how GB phases can be kinetically trapped, enabling atomic-scale room-temperature observations. Our work paves the way for atomic-scale in situ studies of metallic GB phase transformations, which were previously detected only indirectly9,15,27–29, through their influence on abnormal grain growth, non-Arrhenius-type diffusion or liquid metal embrittlement. © 2020, The Author(s), under exclusive licence to Springer Nature Limited.

The thermal conductivity of GeTe crystalline nanowires has been computed by means of non-equilibrium molecular dynamics simulations employing a machine learning interatomic potential. This material is of interest for application in phase change non-volatile memories. The resulting lattice thermal conductivity of an ultrathin nanowire (7.3 nm diameter) of 1.57 W m-1 K-1 is sizably lower than the corresponding bulk value of 3.15 W m-1 K-1 obtained within the same framework. The analysis of the phonon dispersion relations and lifetimes reveals that the lower thermal conductivity in the nanowire is mostly due to a reduction in the phonon group velocities. We further predict the presence of a minimum in the lattice thermal conductivity for thicker nanowires. © 2019 IOP Publishing Ltd.

Global optimization is an active area of research in atomistic simulations, and many algorithms have been proposed to date. A prominent example is basin hopping Monte Carlo, which performs a modified Metropolis Monte Carlo search to explore the potential energy surface of the system of interest. These simulations can be very demanding due to the high-dimensional configurational search space. The effective search space can be reduced by utilizing grids for the atomic positions, but at the cost of possibly biasing the results if fixed grids are employed. In this paper, we present a flexible grid algorithm for global optimization that allows us to exploit the efficiency of grids without biasing the simulation outcome. The method is general and applicable to very heterogeneous systems, such as interfaces between two materials of different crystal structures or large clusters supported at surfaces. As a benchmark case, we demonstrate its performance for the well-known global optimization problem of Lennard-Jones clusters containing up to 100 particles. Despite the simplicity of this model potential, Lennard-Jones clusters represent a challenging test case since the global minima for some "magic" numbers of particles exhibit geometries that are very different from those of clusters with only a slightly different size. © 2020 Author(s).

The synthesis of Li superionic conductor Li7P3S11 may be accompanied by the formation of a detrimental Li4P2S6 phase due to a high mixing sensitivity of precursor materials. This phase exhibits a poor ionic conductivity whose origins are not fully understood. Recently Dietrich et al. investigated the energetics of Li ion migration in Li4P2S6 with nudged elastic band (NEB) calculations. The observed large migration barrier of 0.51 eV for purely interstitial diffusion leads to an interpretation of the low ionic conductivity by kinetic limitations. Based on ab initio molecular dynamics simulations (AIMD) we propose a new and energetically much more favorable diffusion path available to interstitial Li ion charge carriers that has not been considered so far. It consists of a concerted process in which a second lithium atom is pushed out from its equilibrium lattice position by the diffusing lithium ion. A detailed analysis with NEB calculations shows that the energy barrier for this concerted diffusion is only 0.08 eV, i.e. an order of magnitude lower than the previously reported value for purely interstitial diffusion. Therefore, the observed low ionic conductivity of Li4P2S6 is likely not originating from kinetic limitations due to high diffusion barriers but rather from thermodynamic reasons associated with a low concentration of free charge carriers. We therefore expect that increasing the charge carrier concentration by doping is a viable design route to optimize the ionic conductivity of this material. © 2020 The Royal Society of Chemistry.

According to experimental observations, the temperature dependence of self-diffusion coefficient in most body-centered cubic metals (bcc) exhibits non-Arrhenius behavior. The origin of this behavior is likely related to anharmonic vibrational effects at elevated temperatures. However, it is still debated whether anharmonicity affects more the formation or migration of monovacancies, which are known to govern the self-diffusion. In this extensive atomistic simulation study we investigated thermodynamic properties of monovacancies in bcc molybdenum, here taken as a representative model system, from zero temperature to the melting point. We combined first-principles calculations and classical simulations based on three widely used interatomic potentials for Mo. In our analysis we employ static and dynamic atomistic calculations as well as statistical sampling techniques and thermodynamic integration to achieve thorough information about temperature variations of vacancy formation and migration free energies and diffusivities. In addition, we carry out large-scale molecular dynamics simulations that enable direct observation of high-temperature self-diffusion at the atomic scale. By scrutinizing the results obtained by different models and methods, we conclude that the peculiar self-diffusion behavior is likely caused by strong temperature dependence of the vacancy formation energy. © 2020 American Physical Society.

Molecular dynamics simulations are performed to investigate the impact of a coherent Σ3 (111) twin boundary on the plastic deformation behavior of Cu nanopillars. Our work reveals that the mechanical response of pillars with and without the twin boundary is decisively driven by the characteristics of initial dislocation sources. In the condition of comparably large pillar size and abundant initial mobile dislocations, overall yield and flow stresses are controlled by the longest, available mobile dislocation. An inverse correlation of the yield and flow stresses with the length of the longest dislocation is established and compared to experimental data. The experimentally reported subtle differences in yield and flow stresses between pillars with and without the twin boundary are likely related to the maximum lengths of the mobile dislocations. In the condition of comparably small pillar size, for which a reduction of mobile dislocations during heat treatment and mechanical loading occurs, the mechanical response of pillars with and without the twin boundary can be clearly distinguished. Dislocation starvation during deformation is more pronounced in pillars without the twin boundary than in pillars with the twin boundary because the twin boundary acts as a pinning surface for the dislocation network. © 2020 Acta Materialia Inc.

Magnesium is the lowest-density structural metal but has low ductility that limits applications. The low ductility is related to the hexagonally close-packed crystal structure where activation of nonbasal slip is required for general plasticity. Here, our recent neural network potential (NNP) for Mg, trained using Kohn-Sham density functional theory (DFT), is used to examine slip of a dislocations on the prismatic plane. The generalized stacking fault surface energies (GSFEs) for basal and prismatic slip are computed and agree better with Kohn-Sham density functional theory (KS-DFT) than orbital-free density functional theory (OF-DFT) and modified embedded atom method (MEAM), which predict spurious minima. Consistent with the generalized stacking fault energy (GSFE), direct simulations of the prismatic a»screw dislocation show it is unstable to dissociate into the a basal screw dislocation; this is mostly consistent with OF-DFT while MEAM predicts stability. Prismatic slip is thus achieved by a double-cross-slip process of the stable basal dislocations driven by a resolved shear stress on the orthogonal prismatic plane; this is consistent with the process deduced from experiments. The Nudged Elastic Band method is used with the NNP to examine the atomistic path and the stress-dependent enthalpy barrier for this mechanism; this requires many tens of thousands of atoms. The basal-prismatic cross-slip occurs in increments of c/2 via basal constriction, cross-slip on the prism plane, cross-slip back onto the basal plane, and lateral motion of the created jogs to extend the new basal dislocation. Comparisons with experimental deductions show some agreement and some notable disagreement. Resolution of the differences points toward further large-scale studies that require the accuracy and efficiency of KS-DFT-trained NNP, an approach that is also naturally extendable to the important domain of Mg alloys. © 2020 American Chemical Society. All rights reserved.

Amorphization plays an important role in ceramic deformation under mechanical loading. In the present work, we investigate the elasto-plastic deformation mechanisms of monocrystalline cubic silicon carbide (3C–SiC) in spherical nanoindentation by means of molecular dynamics simulations. The indentation-induced amorphization and its interactions with other deformation modes are emphasized. Initially, the suitable empirical potential capable of accurately characterizing the mechanical and defect properties of monocrystalline 3C–SiC, as well as the propensity of phase transformation from 3C–SiC to amorphous SiC, is rationally selected by benchmarking of different empirical potentials with experimental data and density functional theory calculations. Subsequently, the inhomogeneous elastic-plastic transitions during nanoindentation of monocrystalline 3C–SiC, as well as their dependence on crystallographic orientation, are investigated. Phase transformations including amorphization are analyzed using combined methods based on radial distribution function and bond angle distribution. Our simulation results demonstrate that before plasticity initiation-related “pop-in” event, each indented-monocrystalline 3C–SiC experiences a pure quasi-elastic deformation governed by the formation of amorphous structures. And this process of amorphization is fully reversible for small indentation depths. Further amorphization and dislocation nucleation jointly dominate the incipient plasticity in 3C–SiC nanoindentation. It is found that the indentation-induced defect zone composed of amorphous phase and dislocations is more pronounced in 3C–SiC(010) than that in the other two orientations of (110) and (111). © 2020 Elsevier Ltd and Techna Group S.r.l.

Machine learning of the quantitative relationship between local environment descriptors and the potential energy surface of a system of atoms has emerged as a new frontier in the development of interatomic potentials (IAPs). Here, we present a comprehensive evaluation of machine learning IAPs (ML-IAPs) based on four local environment descriptors - atom-centered symmetry functions (ACSF), smooth overlap of atomic positions (SOAP), the spectral neighbor analysis potential (SNAP) bispectrum components, and moment tensors - using a diverse data set generated using high-throughput density functional theory (DFT) calculations. The data set comprising bcc (Li, Mo) and fcc (Cu, Ni) metals and diamond group IV semiconductors (Si, Ge) is chosen to span a range of crystal structures and bonding. All descriptors studied show excellent performance in predicting energies and forces far surpassing that of classical IAPs, as well as predicting properties such as elastic constants and phonon dispersion curves. We observe a general trade-off between accuracy and the degrees of freedom of each model and, consequently, computational cost. We will discuss these trade-offs in the context of model selection for molecular dynamics and other applications. © 2020 American Chemical Society.

Modeling and simulation is transforming modern materials science, becoming an important tool for the discovery of new materials and material phenomena, for gaining insight into the processes that govern materials behavior, and, increasingly, for quantitative predictions that can be used as part of a design tool in full partnership with experimental synthesis and characterization. Modeling and simulation is the essential bridge from good science to good engineering, spanning from fundamental understanding of materials behavior to deliberate design of new materials technologies leveraging new properties and processes. This Roadmap presents a broad overview of the extensive impact computational modeling has had in materials science in the past few decades, and offers focused perspectives on where the path forward lies as this rapidly expanding field evolves to meet the challenges of the next few decades. The Roadmap offers perspectives on advances within disciplines as diverse as phase field methods to model mesoscale behavior and molecular dynamics methods to deduce the fundamental atomic-scale dynamical processes governing materials response, to the challenges involved in the interdisciplinary research that tackles complex materials problems where the governing phenomena span different scales of materials behavior requiring multiscale approaches. The shift from understanding fundamental materials behavior to development of quantitative approaches to explain and predict experimental observations requires advances in the methods and practice in simulations for reproducibility and reliability, and interacting with a computational ecosystem that integrates new theory development, innovative applications, and an increasingly integrated software and computational infrastructure that takes advantage of the increasingly powerful computational methods and computing hardware. © 2020 The Author(s). Published by IOP Publishing Ltd.

We studied grain boundary (GB) self-diffusion in body-centered cubic iron using ab initio calculations and molecular dynamics simulations with various interatomic potentials. A combination of different models allowed us to determine the principal characteristics of self-diffusion along different types of GBs. In particular, we found that atomic self-diffusion in symmetric tilt GBs is mostly driven by self-interstitial atoms. In contrast, in general GBs atoms diffuse predominantly via an exchange mechanism that does not involve a particular defect but is similar to diffusion in a liquid. Most observed mechanisms lead to a significant enhancement of self-diffusion along GBs as compared to diffusion in the bulk. The results of simulations are verified by comparison with available experimental data. © 2020 Acta Materialia Inc.

Binary metal clusters are of high interest for applications in heterogeneous catalysis and have received much attention in recent years. To gain insights into their structure and composition at the atomic scale, computer simulations can provide valuable information if reliable interatomic potentials are available. In this paper we describe the construction of a high-dimensional neural network potential (HDNNP) intended for simulations of large brass nanoparticles with thousands of atoms, which is also applicable to bulk α-brass and its surfaces. The HDNNP, which is based on reference data obtained from density-functional theory calculations, is very accurate with a root-mean-square error of 1.7 meV/atom for total energies and 39 meV Å-1 for the forces of structures not included in the training set. The potential has been thoroughly validated for a wide range of energetic and structural properties of bulk α-brass, its surfaces as well as clusters of different size and composition demonstrating its suitability for large-scale molecular dynamics and Monte Carlo simulations with first-principles accuracy. © 2020 American Chemical Society.

If complex systems are to be studied in molecular simulation, one usually attempts to combine existing interaction models in order to describe the new system. This is, however, not always feasible. We thus propose here a new pairwise-additive interaction model for liquid methanol and solvated Cl− to be used to study the immersion of Metal-Organic Frameworks (MOFs) in methanol. Practically, it entails that all interactions must be written to be compatible with the family of MOF-FF models, which have been specifically developed and then widely employed in molecular simulations of such MOFs, in particular flexible ones. The new model for liquid methanol has been mostly tailored to provide densities and dielectric constants as close to experiment as possible in a large temperature domain. This is important since the flexible MOFs modify their shapes according to their loading with guest molecules of various types, and also according to the thermodynamic conditions. The model yields excellent agreement for the density-temperature, dielectric constant-temperature, and self-diffusion-temperature relationships, properties. Other properties such as e.g. the compressibilities or thermal expansion coefficients are of the correct order of magnitude. Since some MOF frameworks are electrically charged, counterions will be present in these cases. The interactions of Cl− with the liquid are thus also considered here. The solvation of this ion is also found to be satisfactory when compared to other MD studies. © 2019 Elsevier B.V.

An accurate description of reactive scattering of molecules on metal surfaces often requires the modeling of energy transfer between the molecule and the surface phonons. Although ab initio molecular dynamics (AIMD) can describe this energy transfer, AIMD is at present untractable for reactions with reaction probabilities smaller than 1%. Here, we show that it is possible to use a neural network potential to describe a polyatomic molecule reacting on a mobile metal surface with considerably reduced computational effort compared to AIMD. The highly activated reaction of CHD 3 on Cu(111) is used as a test case for this method. It is observed that the reaction probability is influenced considerably by dynamical effects such as the bobsled effect and surface recoil. A special dynamical effect for CHD 3 + Cu(111) is that a higher vibrational efficacy is obtained for two quanta in the CH stretch mode than for a single quantum. Copyright © 2019 American Chemical Society.

Halogenated argyrodites Li6PS5Br, Li6PS5Cl, and Li6PS5I exhibit large differences in the measured Li ionic conductivities. Crystallographic analysis has shown that these differences may be related to occupations of specific Wyckoff sites in different argyrodite types, but detailed understanding of the relationship between the atomic structure and operating diffusion mechanisms is still lacking. In this work, we employed ab initio molecular dynamics simulations to calculate the Li diffusivity for different argyrodite structure types. Our calculations show that the Li diffusivity does not depend implicitly on the type of halogen but is rather governed by the degree of structural disorder. Assuming disordered structures to arise naturally from the ordered structure type by thermally activated antisite defects, we are able to explain the degree of disorder found for the different types of halogens from the calculated defect formation energies. Comparing the calculated formation energies to the ionic radii of the halogen atoms, we find a strong correlation between the radii and energies required for introducing the antisite defects. © 2019 American Chemical Society.

Hydrogenases are metalloenzymes that catalyze the conversion of protons and molecular hydrogen, H2. [FeFe]-hydrogenases show particularly high rates of hydrogen turnover and have inspired numerous compounds for biomimetic H2 production. Two decades of research on the active site cofactor of [FeFe]-hydrogenases have put forward multiple models of the catalytic proceedings. In comparison, our understanding of proton transfer is poor. Previously, residues were identified forming a hydrogen-bonding network between active site cofactor and bulk solvent; however, the exact mechanism of catalytic proton transfer remained inconclusive. Here, we employ in situ infrared difference spectroscopy on the [FeFe]-hydrogenase from Chlamydomonas reinhardtii evaluating dynamic changes in the hydrogen-bonding network upon photoreduction. While proton transfer appears to be impaired in the oxidized state (Hox), the presented data support continuous proton transfer in the reduced state (Hred). Our analysis allows for a direct, molecular unique assignment to individual amino acid residues. We found that transient protonation changes of glutamic acid residue E141 and, most notably, arginine R148 facilitate bidirectional proton transfer in [FeFe]-hydrogenases. © 2019 American Chemical Society.

Interfaces between water and metal oxides exhibit many interesting phenomena like dissociation and recombination of water molecules and water exchange between the interface and the bulk liquid. Moreover, a variety of structural motifs can be found, differing in hydrogen-bonding patterns and molecular orientations. Here, we report the structure and dynamics of liquid water interacting with the two most stable ZnO surfaces, (101Ì) and (112Ì), by means of reactive molecular dynamics simulations based on a machine learning high-dimensional neural network potential. For both surfaces, three distinct hydration layers can be observed within 10 Å from the surface with the first hydration layer (nearest to the surface) representing the most interesting region to investigate. There, water molecules dynamically dissociate and recombine, leading to a variety of chemical species at the interface. We characterized these species and their molecular environments by analyzing the properties of the hydrogen bonds and local geometries. At ZnO(112Ì0), some of the adsorbed hydroxide ions bridge two surface Zn ions, which is not observed at ZnO(101Ì0). For both surfaces, adsorbed water molecules always bind to a single Zn ion, and those located in proximity of the substrate are mostly "H-down" oriented for ZnO(101Ì0) and "flat-lying", i.e., parallel to the surface, for ZnO(112Ì0). The time scales for proton-transfer (PT) reactions are quite similar at the two surfaces, with the average lifetime of adsorbed hydroxide ions being around 41 ± 3 ps until recombination. However, water exchange events, in which adsorbed water molecules leave the surface and enter the bulk liquid, happen more frequently at ZnO(112Ì0) than at ZnO(101Ì0). © 2018 American Chemical Society.

The temperature dependence of vibrational spectra can provide information about structural changes of a system and also serve as a probe to identify different vibrational mode couplings. Fully anharmonic temperature-dependent calculations of these quantities are challenging due to the cost associated with statistically converging trajectory-based methods, especially when accounting for nuclear quantum effects. Here, we train a high-dimensional neural network potential energy surface for the porphycene molecule based on data generated with DFT-B3LYP, including pairwise van der Waals interactions. In addition, we fit a kernel ridge regression model for the molecular dipole moment surface. The combination of this machinery with thermostatted path integral molecular dynamics (TRPMD) allows us to obtain well-converged, full-dimensional, fully-anharmonic vibrational spectra including nuclear quantum effects, without sacrificing the first-principles quality of the potential-energy surface or the dipole surface. Within this framework, we investigate the temperature and isotopologue dependence of the high-frequency vibrational fingerprints of porphycene. While classical-nuclei dynamics predicts a red shift of the vibrations encompassing the NH and CH stretches, TRPMD predicts a strong blue shift in the NH-stretch region and a smaller one in the CH-stretch region. We explain this behavior by analyzing the modulation of the effective potential with temperature, which arises from vibrational coupling between quasi-classical thermally activated modes and high-frequency quantized modes. © 2019 Royal Society of Chemistry. All rights reserved.

Hydrogen pick-up leading to hydride formation is often observed in commercially pure Ti (CP-Ti) and Ti-based alloys prepared for microscopic observation by conventional methods, such as electro-polishing and room temperature focused ion beam (FIB) milling. Here, we demonstrate that cryogenic FIB milling can effectively prevent undesired hydrogen pick-up. Specimens of CP-Ti and a Ti dual-phase alloy (Ti-6Al-2Sn-4Zr-6Mo, Ti6246, in wt.%) were prepared using a xenon-plasma FIB microscope equipped with a cryogenic stage reaching −135 °C. Transmission electron microscopy (TEM), selected area electron diffraction, and scanning TEM indicated no hydride formation in cryo-milled CP-Ti lamellae. Atom probe tomography further demonstrated that cryo-FIB significantly reduces hydrogen levels within the Ti6246 matrix compared with conventional methods. Supported by molecular dynamics simulations, we show that significantly lowering the thermal activation for H diffusion inhibits undesired environmental hydrogen pick-up during preparation and prevents pre-charged hydrogen from diffusing out of the sample, allowing for hydrogen embrittlement mechanisms of Ti-based alloys to be investigated at the nanoscale. © 2019, The Author(s).

Long-range charge transport is important for many applications like batteries, fuel cells, sensors, and catalysis. Obtaining microscopic insights into the atomistic mechanism is challenging, in particular if the underlying processes involve protons as the charge carriers. Here, large-scale reactive molecular dynamics simulations employing an efficient density-functional-theory-based neural network potential are used to unravel long-range proton transport mechanisms at solid-liquid interfaces, using the zinc oxide-water interface as a prototypical case. We find that the two most frequently occurring ZnO surface facets, (1010) and (1120), that typically dominate the morphologies of zinc oxide nanowires and nanoparticles, show markedly different proton conduction behaviors along the surface with respect to the number of possible proton transfer mechanisms, the role of the solvent for long-range proton migration, as well as the proton transport dimensionality. Understanding such surface-facet-specific mechanisms is crucial for an informed bottom-up approach for the functionalization and application of advanced oxide materials. © 2019 The Royal Society of Chemistry.

Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations, and proton disorder. This is made possible by combining advanced free-energy methods and state-of-the-art machine-learning techniques. The ab initio description leads to structural properties in excellent agreement with experiments and reliable estimates of the melting points of light and heavy water. We observe that nuclear-quantum effects contribute a crucial 0.2 meV/H 2 O to the stability of ice Ih, making it more stable than ice Ic. Our computational approach is general and transferable, providing a comprehensive framework for quantitative predictions of ab initio thermodynamic properties using machine-learning potentials as an intermediate step. © 2019 National Academy of Sciences. All rights reserved.

Quantitative and well-targeted design of modern alloys is extremely challenging due to their immense compositional space. When considering only 50 elements for compositional blending the number of possible alloys is practically infinite, as is the associated unexplored property realm. In this paper, we present a simple property-targeted quantitative design approach for atomic-level complexity in complex concentrated and high-entropy alloys, based on quantum-mechanically derived atomic-level pressure approximation. It allows identification of the best suited element mix for high solid-solution strengthening using the simple electronegativity difference among the constituent elements. This approach can be used for designing alloys with customized properties, such as a simple binary NiV solid solution whose yield strength exceeds that of the Cantor high-entropy alloy by nearly a factor of two. This study provides general design rules that enable effective utilization of atomic level information to reduce the immense degrees of freedom in compositional space without sacrificing physics-related plausibility. © 2019, The Author(s).

Recently the possibility of using electric fields as a further stimulus to trigger structural changes in metal-organic frameworks (MOFs) has been investigated. In general, rotatable groups or other types of mechanical motion can be driven by electric fields. In this study we demonstrate how the electric response of MOFs can be tuned by adding rotatable dipolar linkers, generating a material that exhibits paraelectric behavior in two dimensions and dielectric behavior in one dimension. The suitability of four different methods to compute the relative permittivity κ by means of molecular dynamics simulations was validated. The dependency of the permittivity on temperature T and dipole strength μ was determined. It was found that the herein investigated systems exhibit a high degree of tunability and substantially larger dielectric constants as expected for MOFs in general. The temperature dependency of κ obeys the Curie-Weiss law. In addition, the influence of dipolar linkers on the electric field induced breathing behavior was investigated. With increasing dipole moment, lower field strengths are required to trigger the contraction. These investigations set the stage for an application of such systems as dielectric sensors, order-disorder ferroelectrics, or any scenario where movable dipolar fragments respond to external electric fields. Copyright © 2019 American Chemical Society.

The displacive phase transformation of metal-organic frameworks (MOFs), referred to as “breathing,” is computationally investigated intensively within periodic boundary conditions (PBC). In contrast, the first-principles parameterized force field MOF-FF is used to investigate the thermal- and pressure-induced transformations for non-periodic nanocrystallites of DMOF-1 (Zn2(bdc)2(dabco); bdc: 1,4-benzenedicarboxylate; dabco: 1,4-diazabicyclo[2.2.2]octane) as a model system to investigate the effect of the PBC approximation on the systems' kinetics and thermodynamics and to assess whether size effects can be captured by this kind of simulation. By the heating of differently sized closed pore nanocrystallites, a spontaneous opening is observed with an interface between the closed and open pore phase moving rapidly through the system. The nucleation temperature for the opening transition rises with size. By enforcing the phase transition with a distance restraint, the free energy can be quantified via umbrella sampling. The apparent barrier is substantially lower than for a concerted process under PBC. Interestingly, the barrier reduces with the size of the nanocrystallite, indicating a hindering surface effect. The results demonstrate that the actual free energy barriers and the importance of surface effects for the transformation under real conditions can only be studied beyond PBC. © 2019 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Anisotropy is one central influencing factor on achievable ultimate machined surface integrity of metallic materials. Specifically, grain boundary has a strong impact on the deformation behaviour of polycrystalline materials and correlated material removal at the microscale. In the present work, we perform molecular dynamics simulations and experiments to elucidate the underlying grain boundary-associated mechanisms and their correlations with machining results of a bi-crystal Cu under nanocutting using a Berkovich tool. Specifically, crystallographic orientations of simulated bi-crystal Cu with a misorientation angle of 44.1° are derived from electron backscatter diffraction characterization of utilized polycrystalline copper specimen. Simulation results reveal that blocking of dislocation motion at grain boundaries, absorption of dislocations by grain boundaries and dislocation nucleation from grain boundaries are operating deformation modes in nanocutting of the bi-crystal Cu. Furthermore, heterogeneous grain boundary-associated mechanisms in neighbouring grains lead to strong anisotropic machining behaviour in the vicinity of the grain boundary. Simulated machined surface morphology and machining force evolution in the vicinity of grain boundary qualitatively agree well with experimental results. It is also found that the geometry of Berkovich tool has a strong impact on grain boundary-associated mechanisms and resultant ploughing-induced surface pile-up phenomenon. © 2019 The Author(s). Published by IOP Publishing Ltd on behalf of the IMMT

The adsorption of gas-phase pyruvic acid (CH 3 COCOOH) on hydroxylated silica particles has been investigated at 296 K using transmission Fourier transform infrared (FTIR) spectroscopy and theoretical simulations. Under dry conditions (<1% relative humidity, RH), both the trans-cis (Tc) and trans-trans (Tt) pyruvic acid conformers are observed on the surface as well as the (hydrogen bonded) pyruvic acid dimer. The detailed surface interactions were further understood through ab initio molecular dynamics simulations. Under higher relative humidity conditions (above 10% RH), adsorbed water competes for surface adsorption sites. Adsorbed water is also observed to change the relative populations of the different adsorbed pyruvic acid configurations. Overall, this study provides valuable insights into the interaction of pyruvic acid with hydroxylated silica surfaces on the molecular level from both experimental and theoretical analyses. Furthermore, these results highlight the importance of the environment (relative humidity and coadsorbed water) in the adsorption, partitioning, and configurations of pyruvic acid at the surface. Copyright © 2019 American Chemical Society.

This paper reports on the first ab initio molecular dynamics study of the ferroelectric sodium nitrite, shedding light on its ferroelctric-paraelectric phase transition. The remnant polarization Pr was calculated using a Mulliken population analysis and maximally localized Wannier functions. Especially the Wannier based model is in outstanding agreement with experimental findings and previous Berry phase calculations. The simulations predict a ferroelectric Curie temperature Tc between 425 and 450K in excellent agreement with the experimental value of 437K. In addition, the anomalous lattice behavior (shrinking of the c axis) during the phase transition is reproduced. Furthermore, the analysis of the phase transition revealed a combined displacive and order-disorder mechanism. The crystal field effect in the material could be quantified by investigating the molecular dipoles based on the maximally localized Wannier functions and the intermolecular charge transfer by analyzing the Mulliken charges. In agreement with earlier experimental and theoretical findings, the polarization reversal mechanism was found to be dominated by a c-axis rotation of the nitrite ions. The molecular insight into such a simple and prototypical material serves as a basis for a further development of more complex crystalline ferroelectrics, using a design principle inspired by NaNO2. © 2019 American Physical Society.

Recent experiments provide evidence for density variations along shear bands in metallic glasses with a length scale of a few hundred nanometers. Via molecular dynamics simulations of a generic binary glass model, here we show that this is strongly correlated with variations of composition, coordination number, viscosity, and heat generation. Individual shear events along the shear band path show a mean distance of a few nanometers, comparable to recent experimental findings on medium range order. The aforementioned variations result from these localized perturbations, mediated by elasticity. © 2019 American Physical Society.

Dislocation-precipitate interaction and solute segregation play important roles in controlling the mechanical behavior of Ni-based superalloys at high temperature. In particular, the increased mobility of solutes at high temperature leads to increased dislocation-solute interaction. For example, atom probe tomography (APT) results [1] for single crystal MC2 superalloy indicate significant segregation of solute elements such as Co and Cr to dislocations and stacking faults in γ′ precipitates. To gain further insight into solute segregation, dislocation-solute interaction, and its effect on the mechanical behavior in such Ni-superalloys, finite-deformation phase field chemomechanics [2] is applied in this work to develop a model for dislocation-solute-precipitate interaction in the two-phase γ-γ′ Ni-based superalloy model system Ni–Al–Co. Identification and quantification of this model is based in particular on the corresponding Ni–Al–Co embedded atom method (EAM) potential [3]. Simulation results imply both Cottrell- and Suzuki-type segregation of Co in γ and γ'. Significant segregation of Co to dislocation cores and faults in γ′ is also predicted, in agreement with APT results. Predicted as well is the drag of Co by γ dislocations entering and shearing γ'. Since solute elements such as Co generally prefer the γ phase, Co depletion in γ′ could be reversed by such dislocation drag. The resulting change in precipitate chemistry may in turn affect its stability and play a role in precipitate coarsening and rafting. © 2019 Acta Materialia Inc.

We present an approach that enables an efficient and accurate study of dynamically unstable crystals over the full temperature range. The approach is based on an interatomic potential fitted to ab initio molecular dynamics energies for both the high- and low-temperature stable phases. We verify by comparison to explicit ab initio simulations that such a bespoke potential, for which we use here the functional form of the embedded atom method, provides accurate transformation temperatures and atomistic features of the transformation. The accuracy of the potential makes it an ideal tool to study the important impact of finite size and finite time effects. We apply our approach to the dynamically unstable β (bcc) titanium phase and study in detail the transformation to the low-temperature stable hexagonal ω phase. We find a large set of previously unreported linear-chain disordered (LCD) structures made up of three types of [111]β linear-chain defects that exhibit randomly disordered arrangements in the (111)β plane. © 2019 American Physical Society.

Effect of small additive molecules on the structural relaxation of polymer melts is investigated via molecular dynamics simulations. At a constant external pressure and a fixed number concentration of added molecules, the variation of the particle diameter leads to a non-monotonic change of the relaxation dynamics of the polymer melt. For non-entangled chains, this effect is rationalized in terms of an enhanced added-particle-dynamics which competes with a weaker coupling strength upon decreasing the particle size. Interestingly, cooling simulations reveal a non-monotonic effect on the glass transition temperature also for entangled chains, where the effect of additives on polymer dynamics is more intricate. This observation underlines the importance of monomer-scale packing effects on the glass transition in polymers. In view of this fact, size-adaptive thermosensitive core-shell colloids would be a promising candidate route to explore this phenomenon experimentally. © 2019 Author(s).

Reversible martensitic transformations (MTs) are the origin of many fascinating phenomena, including the famous shape memory effect. In this work, we present a fully ab initio procedure to characterize MTs in alloys and to assess their reversibility. Specifically, we employ ab initio molecular dynamics data to parametrize a Landau expansion for the free energy of the MT. This analytical expansion makes it possible to determine the stability of the high- and low-temperature phases, to obtain the Ehrenfest order of the MT, and to quantify its free energy barrier and latent heat. We apply our model to the high-temperature shape memory alloy Ti-Ta, for which we observe remarkably small values for the metastability region (the interval of temperatures in which the high- and low-temperature phases are metastable) and for the barrier: these small values are necessary conditions for the reversibility of MTs and distinguish shape memory alloys from other materials. © 2019 American Physical Society.

Strategies to reduce the incubation time for crystal nucleation and thus the stochasticity of the set process are of relevance for the operation of phase change memories in ultra-scaled geometries. With these premises, in this work we investigate the crystallization kinetics of the phase change compound GeTe. We have performed large scale molecular dynamics simulations using an interatomic potential, generated previously from a neural network fitting of a database of ab initio energies. We have addressed the crystallization of models of amorphous GeTe annealed at different temperatures above the glass transition. The results on the distribution of subcritical nuclei and on the crystal growth velocity of postcritical ones are compared with our previous simulations of the supercooled liquid quenched from the melt. We find that a large population of subcritical nuclei can form at the lower temperatures where the nucleation rate is large. This population partially survives upon fast annealing, which leads to a dramatic reduction of the incubation time at high temperatures where the crystal growth velocity is maximal. This priming effect could be exploited to enhance the speed of the set process in phase change memories. © 2019 The Royal Society of Chemistry.

Gold nanoparticles supported on reduced TiO2 (110) surfaces are widely used as catalysts for oxidation reactions. Despite extensive studies, the role of oxygen vacancies in such systems remains elusive and is controversially discussed. Combining ab initio molecular dynamics simulations with methods originally developed to describe defects in semiconductor physics we study how the electronic charge originally located at the vacancy modifies the charge on the cluster. Despite differences resulting from the employed level of density functional theory (namely semilocal/GGA, GGA + U, and hybrid functionals), we consistently find that the Au clusters remain either neutral or acquire a positive charge. The intuitively expected electron transfer from the oxygen vacancy to the gold cluster can be safely ruled out. Analyzing these findings, we discuss the role of the oxygen vacancy in the bonding between Au clusters and support and the catalytic activity of the system. © 2019 American Chemical Society.

Background: Silica continues to represent an intriguing topic of fundamental and applied research across various scientific fields, from geology to physics, chemistry, cell biology, and particle toxicology. The pathogenic activity of silica is variable, depending on the physico-chemical features of the particles. In the last 50 years, crystallinity and capacity to generate free radicals have been recognized as relevant features for silica toxicity. The 'surface' also plays an important role in silica toxicity, but this term has often been used in a very general way, without defining which properties of the surface are actually driving toxicity. How the chemical features (e.g., silanols and siloxanes) and configuration of the silica surface can trigger toxic responses remains incompletely understood. Main body: Recent developments in surface chemistry, cell biology and toxicology provide new avenues to improve our understanding of the molecular mechanisms of the adverse responses to silica particles. New physico-chemical methods can finely characterize and quantify silanols at the surface of silica particles. Advanced computational modelling and atomic force microscopy offer unique opportunities to explore the intimate interactions between silica surface and membrane models or cells. In recent years, interdisciplinary research, using these tools, has built increasing evidence that surface silanols are critical determinants of the interaction between silica particles and biomolecules, membranes, cell systems, or animal models. It also has become clear that silanol configuration, and eventually biological responses, can be affected by impurities within the crystal structure, or coatings covering the particle surface. The discovery of new molecular targets of crystalline as well as amorphous silica particles in the immune system and in epithelial lung cells represents new possible toxicity pathways. Cellular recognition systems that detect specific features of the surface of silica particles have been identified. Conclusions: Interdisciplinary research bridging surface chemistry to toxicology is progressively solving the puzzling issue of the variable toxicity of silica. Further interdisciplinary research is ongoing to elucidate the intimate mechanisms of silica pathogenicity, to possibly mitigate or reduce surface reactivity. © 2019 The Author(s).

Purpose: This paper aims to reveal the mechanism for improving ductile machinability of 3C-silicon carbide (SiC) and associated cutting mechanism in stress-assisted nanometric cutting. Design/methodology/approach: Molecular dynamics simulation of nano-cutting 3C-SiC is carried out in this paper. The following two scenarios are considered: normal nanometric cutting of 3C-SiC; and stress-assisted nanometric cutting of 3C-SiC for comparison. Chip formation, phase transformation, dislocation activities and shear strain during nanometric cutting are analyzed. Findings: Negative rake angle can produce necessary hydrostatic stress to achieve ductile removal by the extrusion in ductile regime machining. In ductile-brittle transition, deformation mechanism of 3C-SiC is combination of plastic deformation dominated by dislocation activities and localization of shear deformation. When cutting depth is greater than 10 nm, material removal is mainly achieved by shear. Stress-assisted machining can lead to better quality of machined surface. However, there is a threshold for the applied stress to fully gain advantages offered by stress-assisted machining. Stress-assisted machining further enhances plastic deformation ability through the active dislocations’ movements. Originality/value: This work describes a stress-assisted machining method for improving the surface quality, which could improve 3C-SiC ductile machining ability. © 2019, Emerald Publishing Limited.

Unraveling the atomistic details of solid/liquid interfaces, e.g., by means of vibrational spectroscopy, is of vital importance in numerous applications, from electrochemistry to heterogeneous catalysis. Water-oxide interfaces represent a formidable challenge because a large variety of molecular and dissociated water species are present at the surface. Here, we present a comprehensive theoretical analysis of the anharmonic OH stretching vibrations at the water/ZnO(1010) interface as a prototypical case. Molecular dynamics simulations employing a reactive high-dimensional neural network potential based on density functional theory calculations have been used to sample the interfacial structures. In the second step, one-dimensional potential energy curves have been generated for a large number of configurations to solve the nuclear Schrödinger equation. We find that (i) the ZnO surface gives rise to OH frequency shifts up to a distance of about 4 Å from the surface; (ii) the spectrum contains a number of overlapping signals arising from different chemical species, with the frequencies decreasing in the order ν(adsorbed hydroxide) > ν(non-adsorbed water) > ν(surface hydroxide) > ν(adsorbed water); (iii) stretching frequencies are strongly influenced by the hydrogen bond pattern of these interfacial species. Finally, we have been able to identify substantial correlations between the stretching frequencies and hydrogen bond lengths for all species. © 2018 Author(s).

The adsorption of GLY-PRO-GLU tripeptide on Au(110) is investigated within the frame of all atom classical mechanics simulations and Density Functional Theory, focusing on the surface reconstruction. It is shown that the tripeptide adsorption reorganizes and restructures the Au(110) surface. A mechanism for the surface restructuration is proposed for both the neutral and zwitterionic form of the peptide at room temperature in Ultra High Vacuum. Diverse residues may be involved in the Au atoms displacement, and in particular glutamic acid, triggering a double proton transfer and the formation of a zwitter ionic state, is found to be responsible for the triggering of the surface reconstruction. © 2018 Elsevier B.V.

Nuclear quantum effects (NQEs) cause the nuclei of light elements like hydrogen to delocalize, affecting numerous properties of water and aqueous solutions, such as hydrogen-bonding and proton transfer barriers. Here, we address the prototypical case of aqueous NaOH solutions by investigating the effects of quantum nuclear fluctuations on radial distribution functions, hydrogen-bonding geometries, power spectra, proton transfer barriers, proton transfer rates, water self-exchange rates around the Na+ cations, and diffusion coefficients, for the full room-temperature solubility range. These properties were calculated from classical and ring-polymer molecular dynamics simulations employing a reactive high-dimensional neural network potential based on dispersion-corrected density functional theory reference calculations. We find that NQEs have a very small impact on the solvation structure around Na+, slightly strengthen the water-water and water-hydroxide hydrogen bonds, and lower the peak positions in the power spectra for the HOH bending and OH stretching modes by about 50 and 100 cm-1, respectively. Moreover, NQEs significantly lower the proton transfer barriers, thus increasing the proton transfer rates, resulting in an increase of the diffusion coefficient in particular of OH-, as well as a decrease of the mean residence time of molecules in the first hydration shell around Na+ at high NaOH concentrations. © 2018 American Chemical Society.

Low carbon steels undergo strain aging when heat treated, which causes an increased yield strength that can be observed macroscopically. Such strengthening mechanism is driven by atomistic scale processes, i.e., solute segregation of carbon (C) or nitrogen interstitial atoms. Due to its low solubility, alloying elements can diffuse to defects (e.g., dislocations) and form the so-called Cottrell atmospheres. Consequently, the mobility of defects is strongly reduced because of the interaction with solutes, and higher stresses are needed to unpin them from the Cottrell atmosphere. As C segregation and atomistic motion take place at separate timescales, Classical Molecular Dynamics (MD) and Metropolis Monte Carlo (MC) are coupled in a unified framework to capture collective effects with underlying slow dynamics. The number of degrees of freedom and the need for large computational resources in this simulation requires the choice of an optimal parallelization technique for the MC part of such multi-scale simulations using an unbiased sampling of the configuration space. In the present work, two different parallel approaches for the MC routine applied to the simulation of Cottrell atmospheres are implemented and compared: (i) a manager-worker speculative scheme and (ii) a distributed manager-worker over a cell-based domain decomposition approach augmented by an efficient load balancing scheme. The parallel performance of different Fe-C containing defects with several millions of atoms is analyzed, and also the possible optimization of the efficiency of the MC solute segregation process is evaluated regarding energy minimization. © 2018 Elsevier B.V.

Classical molecular dynamics simulation for atomistic systems is implemented in OpenCL and benchmarked on a variety of different hardware platforms. Modifying the number of particles and system size in the study provides insight into characteristics of parallel compute platforms, where latency, data transfer, memory access characteristics and compute intense work can be identified as fingerprints in benchmark runs. Data layouts are compared, for which the access of structure-of-arrays shows best performance in most cases. It is demonstrated that function portability can be achieved straightforwardly with OpenCL, while performance portability lacks behind as various architectures strongly depend on specific vectorisation optimisation. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Analysis and design of materials and fluids requires understanding of the fundamental relationships between structure, composition, and properties. Dislocations and grain boundaries influence microstructure evolution through the enhancement of diffusion and by facilitating heterogeneous nucleation, where atoms must overcome a potential barrier to enable the early stage of formation of a phase. Adsorption and spinodal decomposition are known precursor states to nucleation and phase transition; however, nucleation remains the less well-understood step in the complete thermodynamic sequence that shapes a microstructure. Here, we report near-atomic-scale observations of a phase transition mechanism that consists in solute adsorption to crystalline defects followed by linear and planar spinodal fluctuations in an Fe-Mn model alloy. These fluctuations provide a pathway for austenite nucleation due to the higher driving force for phase transition in the solute-rich regions. Our observations are supported by thermodynamic calculations, which predict the possibility of spinodal decomposition due to magnetic ordering. © 2018 The Author(s).

Precipitation is an efficient method to strengthen metallic materials. While precipitation hardening effects on dislocation slip have been studied extensively in the past, the influence of precipitates on twinning mediated plasticity and the development of corresponding hardening models that account for twin-precipitate interactions have received less attention. Here, the interaction of {10-12} extension twin boundaries (TBs) in pure magnesium with precipitates of plate-, sphere- and rod-like shapes is studied using molecular dynamics (MD) simulations. We find that TBs that engulf precipitates are absorbed by the precipitate-matrix interfaces, and the precipitates are neither twinned nor sheared but deform elastically leading to their rotation. TBs can pass small precipitates (length? 20 nm) and remain intact. In contrast when TBs are interacting with large precipitates (length? 50 nm), basal dislocations or stacking faults nucleate from the interfaces, causing local plastic relaxation. The stress field around a plate-like precipitate as calculated in the MD simulations suggests that a strong back-stress is imposed on the TBs. We then coarse grain these mechanisms into an analytical mean field model of precipitation hardening on twinning in magnesium alloys, which is based on the energy conservation during the TB-precipitate interaction. The model is in good agreement with the current MD simulations and published experimental observations. The hardening model shows that spherical precipitates have the strongest hardening effect on twinning, basal and prismatic plate-like precipitates have a medium effect while rod-like precipitates exert the weakest influence. We also find that most types of precipitates show a stronger hardening effect on twinning mediated plasticity than on basal dislocation slip. Finally, prismatic plate-like precipitates are predicted to have reasonable hardening effects on both twinning and basal slip. These results can help guiding the development of magnesium alloys with enhanced strength and ductility. © 2018 Elsevier Ltd.

We present a measurement cell that allows simultaneous measurement of second harmonic generation (SHG) and streaming potential (SP) at mineral-water interfaces with flat specimen that are suitable for non-linear optical (NLO) studies. The set-up directly yields SHG data for the interface of interest and can also be used to obtain information concerning the influence of flow on NLO signals from that interface. The streaming potential is at present measured against a reference substrate (PTFE). The properties of this inert reference can be independently determined for the same conditions. With the new cell, for the first time the SHG signal and the SP for flat surfaces have been simultaneously measured on the same surface. This can in turn be used to unambiguously relate the two observations for identical solution composition. The SHG test of the cell with a fluorite sample confirmed previously observed differences in NLO signal under flow vs. no flow conditions in sum frequency generation (SFG) investigations. As a second test surface, an inert (“hydrophobic”) OTS covered sapphire-c electrolyte interface was studied to verify the zeta-potential measurements with the new cell. For this system we obtained combined zeta-potential/SHG data in the vicinity of the point of zero charge, which were found to be proportional to each other as expected. Furthermore, on the accessible time scales of the SHG measurements no effects of flow, flow velocity and stopped flow occurred on the interfacial water structure. This insensitivity to flow for the inert surface was corroborated by concomitant molecular dynamics simulations. Finally, the set-up was used for simultaneous measurements of the two properties as a function of pH in automated titrations with an oxidic surface. Different polarization combinations obtained in two separate titrations, yielded clearly different SHG data, while under identical conditions zeta-potentials were exactly reproduced. The polarization combination that is characteristic for dipoles perpendicular to the surface scaled with the zeta-potentials over the pH-range studied, while the other did not. The work provides an advanced approach for investigating liquid/surface interactions which play a major role in our environment. The set-up can be upgraded for SFG studies, which will allow more detailed studies on the chemistry and the water structure at a given interface, but also the combined study of specific adsorption including kinetics in combination with electrokinetics. Such investigations are crucial for the basic understanding of many environmental processes from aquatic to atmospheric systems. © 2018 Elsevier Inc.

Metallic nanostructures have become popular for applications in therapeutics, catalysts, imaging, and gene delivery. Molecular dynamics simulations are gaining influence to predict nanostructure assembly and performance; however, instantaneous polarization effects due to induced charges in the free electron gas are not routinely included. Here we present a simple, compatible, and accurate polarizable potential for gold that consists of a Lennard-Jones potential and a harmonically coupled core-shell charge pair for every metal atom. The model reproduces the classical image potential of adsorbed ions as well as surface, bulk, and aqueous interfacial properties in excellent agreement with experiment. Induced charges affect the adsorption of ions onto gold surfaces in the gas phase at a strength similar to chemical bonds while ions and charged peptides in solution are influenced at a strength similar to intermolecular bonds. The proposed model can be applied to complex gold interfaces, electrode processes, and extended to other metals. © 2018 The Author(s).

Quantum coherence of superposed states, especially of entangled states, is indispensable for many quantum technologies. However, it is vulnerable to environmental noises, posing a fundamental challenge in solid-state systems including spin qubits. Here we show a scheme of entanglement engineering where pure dephasing assists the generation of quantum entanglement at distant sites in a chain of electron spins confined in semiconductor quantum dots. One party of an entangled spin pair, prepared at a single site, is transferred to the next site and then adiabatically swapped with a third spin using a transition across a multi-level avoided crossing. This process is accelerated by the noise-induced dephasing through a variant of the quantum Zeno effect, without sacrificing the coherence of the entangled state. Our finding brings insight into the spin dynamics in open quantum systems coupled to noisy environments, opening an avenue to quantum state manipulation utilizing decoherence effects. © 2018 The Author(s).

Using molecular dynamics simulations based on ab initio trained high-dimensional neural network potentials, we study the equation of state of liquid water at negative pressures. From density isobars computed for various pressures down to p = -230 MPa we determine the line of density maxima for two potentials based on the BLYP and the RPBE functionals, respectively. In both cases, dispersion corrections are included to account for non-local long-range correlations that give rise to van der Waals forces. We have followed the density maximum down to negative pressures close to the spinodal instability. For both functionals, the temperature of maximum density increases with decreasing pressure under moderate stretching, but changes slope at P ≈ -200 MPa and p ≈ -20 MPa for BLYP and RPBE, respectively. Our calculations confirm qualitatively the retracing shape of the line of density maxima found for empirical water models, indicating that the spinodal line maintains a positive slope even at strongly negative pressures. © 2018 IOP Publishing Ltd.

Ion implantation is one of the best methods to manufacture silicon-vacancy (SiV) centers in diamond, which can be used as qubits. In this work, molecular dynamics (MD) simulation was conducted to analyze the damage evolution and distribution during the process of silicon ion implantation into bulk diamond and subsequent annealing. Tersoff-ZBL (Ziegler-Biersack-Littmark) potential was used to describe the atomic interaction. Identify Diamond Structure (IDS) and Wigner-Seitz defect analysis methods were used to calculate damages and vacancies. After 2393 K annealing, about 42.5% of ion induced IDS damages were recovered. During the temperature cooling down from 2393 K to 293 K, the movements of silicon atoms along the implantation direction were sensitive to the temperature variation, while vacancies were almost insensitive. MD simulation is helpful to illustrate the ion implant induced damages’ dynamic evolution and Si-V related defects, which can assist a deeper understanding of SiV center's manufacturing. © 2018 Elsevier B.V.

Molecular dynamics simulations, using a classical force field model, have been used to determine the dependence of the static relative dielectric constant of ion solutions with respect to the nature and concentration of the ions and the field strength. The experimentally observed effect of a reduction of the dielectric permittivity due to solvated ions is known as dielectric decrement. We used both the polarization fluctuation at zero field and the constant dielectric displacement method for finite fields to determine the dielectric constant of the bulk solution. All the experimentally observed tendencies of the dielectric decrement could be qualitatively reproduced. The analysis of different solute solvent radial distribution functions indicate that the dielectric decrement arises from the competition between the macroscopic electric field and the local water-ion interaction. The results suggest that the electric field eventually manages to overcome the local molecular interactions, breaking up the structure of the solvation shell and thus lowering the ion's effect on the dielectric constant. This effect seems to correlate with the solvation energy of the individual ions as well as the type of counter ion, indicating that also long range interactions might play a role. The results can be used to improve especially continuum electrolyte models, used to study electrochemical interfaces, where currently the dielectric decrement is generally not included. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

At the interface, the properties of water can be rather different from those observed in the bulk. In this chapter we present an overview of our computational approach to understand water structure and dynamics at the interface including atomistic and electronic structure details. In particular we show how Density Functional Theory-based molecular dynamics simulations (DFT-MD) of water interfaces can provide a microscopic interpretation of recent experimental results from surface sensitive vibrational Sum Frequency Generation spectroscopy (SFG). In our recent work we developed an expression for the calculation of the SFG spectra of water interfaces which is based on the projection of the atomic velocities on the local normal modes. Our approach permits to obtain the SFG signal from suitable velocity-velocity correlation functions, reducing the computational cost to that of the accumulation of a molecular dynamics trajectory, and therefore cutting the overhead costs associated to the explicit calculation of the dipole moment and polarizability tensor. Our method permits to interpret the peaks in the spectrum in terms of local modes, also including the bending region. The results for the water-air interface, obtained using extensive ab initio molecular dynamics simulations over 400 ns, are discussed in connection to recent phase resolved experimental data. © Springer International Publishing AG 2018.

Although they have been widely used as models for oxide surfaces, the deprotonation behaviors of the Keggin-ions (MeAl127+) and typical oxide surfaces are very different. On Keggin-ions, the deprotonation occurs over a very narrow pH range at odds with the broad charging curve of larger oxide surfaces. Depending on the Me concentration, the deprotonation curve levels off sooner (high Me concentration) or later (for low Me concentration). The leveling off shows the onset of aggregation before which the Keggin-ions are present as individual units. We show that the atypical titration data previously observed for some GaAl12 solutions in comparison to the originally reported data can be explained by the presence of Ga2Al11 ions. The pKa value of aquo-groups bound to octahedral Ga was determined from ab initio molecular dynamics simulations relative to the pure GaAl12 ions. Using these results within a surface complexation model, the onset of deprotonation of the crude solution is surprisingly well predicted and the ratio between the different species is estimated to be in the proportion 20 (Ga2Al11): 20 (Al13): 60 (GaAl12). © 2018 Author(s).

The unmatched catalytic turnover rates of [FeFe]-hydrogenases require an exceptionally efficient proton-transfer (PT) pathway to shuttle protons as substrates or products between bulk water and catalytic center. For clostridial [FeFe]-hydrogenase CpI such a pathway has been proposed and analyzed, but mainly on a theoretical basis. Here, eleven enzyme variants of two different [FeFe]-hydrogenases (CpI and HydA1) with substitutions in the presumptive PT-pathway are examined kinetically, spectroscopically, and crystallographically to provide solid experimental proof for its role in hydrogen-turnover. Targeting key residues of the PT-pathway by site directed mutagenesis significantly alters the pH-activity profile of these variants and in presence of H2 their cofactor is trapped in an intermediate state indicative of precluded proton-transfer. Furthermore, crystal structures coherently explain the individual levels of residual activity, demonstrating e.g. how trapped H2O molecules rescue the interrupted PT-pathway. These features provide conclusive evidence that the targeted positions are indeed vital for catalytic proton-transfer. © 2018, The Author(s).

The excitation of electron-hole pairs in reactive scattering of molecules at metal surfaces often affects the physical and dynamical observables of interest, including the reaction probability. Here, we study the influence of electron-hole pair excitation on the dissociative chemisorption of N2 on Ru(0001) using the local density friction approximation method. The effect of surface atom motion has also been taken into account by a high-dimensional neural network potential. Our nonadiabatic molecular dynamics simulations with electronic friction show that the reaction of N2 is more strongly affected by the energy transfer to surface phonons than by the energy loss to electron-hole pairs. The discrepancy between the computed reaction probabilities and experimental results is within the experimental error both with and without friction; however, the incorporation of electron-hole pairs yields somewhat better agreement with experiments, especially at high collision energies. We also calculate the vibrational efficacy for the N2 + Ru(0001) reaction and demonstrate that the N2 reaction is more enhanced by exciting the molecular vibrations than by adding an equivalent amount of energy into translation. © 2018 American Chemical Society.

3-Hydroxy-3-methylglutaryl–coenzyme A (HMG-CoA) reductase was investigated in different organic cosolvents by means of kinetic and calorimetric measurements, molecular dynamics simulations, and small-angle X-ray scattering. The combined experimental and theoretical techniques were essential to complement each other's limitations in the investigation of the complex interaction pattern between the enzyme, different solvent types, and concentrations. In this way, the underlying mechanisms for the loss of enzyme activity in different water-miscible solvents could be elucidated. These include direct inhibitory effects onto the active center and structural distortions. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

As shown by a quite significant amount of literature, acids at the water surface tend to be "less" acid, meaning that their associated form is favored over the conjugated base. What happens at the solid/liquid interface? In the case of the silica/water interface, we show how the acidity of adsorbed molecules can instead increase. Using a free energy perturbation approach in combination with electronic structure-based molecular dynamics simulations, we show how the acidity of pyruvic acid at the quartz/water interface is increased by almost two units. Such increased acidity is the result of the specific microsolvation at the interface and, in particular, of the stabilization of the deprotonated form by the silanols on the quartz surface and the special interfacial water layer. © 2018 American Chemical Society.

Field ion microscopy allows for direct imaging of surfaces with true atomic resolution. The high charge density distribution on the surface generates an intense electric field that can induce ionization of gas atoms. We investigate the dynamic nature of the charge and the consequent electrostatic field redistribution following the departure of atoms initially constituting the surface in the form of an ion, a process known as field evaporation. We report on a new algorithm for image processing and tracking of individual atoms on the specimen surface enabling quantitative assessment of shifts in the imaged atomic positions. By combining experimental investigations with molecular dynamics simulations, which include the full electric charge, we confirm that change is directly associated with the rearrangement of the electrostatic field that modifies the imaging gas ionization zone. We derive important considerations for future developments of data reconstruction in 3D field ion microscopy, in particular for precise quantification of lattice strains and characterization of crystalline defects at the atomic scale. © 2018 IOP Publishing Ltd.

What happens when extra vibrational energy is added to water? Using nonequilibrium molecular dynamics simulations, also including the full electronic structure, and novel descriptors, based on projected vibrational density of states, we are able to follow the flow of excess vibrational energy from the excited stretching and bending modes. We find that the energy relaxation, mostly mediated by a stretching-stretching coupling in the first solvation shell, is highly heterogeneous and strongly depends on the local environment, where a strong hydrogen bond network can transport energy with a time scale of 200 fs, whereas a weaker network can slow down the transport by a factor 2-3. Copyright © 2018 American Chemical Society.

We study the mutual coupling of spin fluctuations and lattice vibrations in paramagnetic CrN by combining atomistic spin dynamics and ab initio molecular dynamics. The two degrees of freedom are dynamically coupled, leading to nonadiabatic effects. Those effects suppress the phonon lifetimes at low temperature compared to an adiabatic approach. The dynamic coupling identified here provides an explanation for the experimentally observed unexpected temperature dependence of the thermal conductivity of magnetic semiconductors above the magnetic ordering temperature. © 2018 American Physical Society.

Room temperature ionic liquids (RTILs) have been shown to exhibit spatial heterogeneity or structural heterogeneity in the sense that they form hydrophobic and ionic domains. Yet studies of the relationship between this structural heterogeneity and the ∼picosecond motion of the molecular constituents remain limited. In order to obtain insight into the time scales relevant to this structural heterogeneity, we perform molecular dynamics simulations of a series of RTILs. To investigate the relationship between the structures, i.e., the presence of hydrophobic and ionic domains, and the dynamics, we gradually increase the size of the hydrophobic part of the cation from ethylammonium nitrate (EAN), via propylammonium nitrate (PAN), to butylammonium nitrate (BAN). The two ends of the organic cation, namely, the charged Nhead-H group and the hydrophobic Ctail-H group, exhibit rotational dynamics on different time scales, evidencing dynamical heterogeneity. The dynamics of the Nhead-H group is slower because of the strong coulombic interaction with the nitrate counter-ionic anions, while the dynamics of the Ctail-H group is faster because of the weaker van der Waals interaction with the surrounding atoms. In particular, the rotation of the Nhead-H group slows down with increasing cationic chain length, while the rotation of the Ctail-H group shows little dependence on the cationic chain length, manifesting that the dynamical heterogeneity is enhanced with a longer cationic chain. The slowdown of the Nhead-H group with increasing cationic chain length is associated with a lower number of nitrate anions near the Nhead-H group, which presumably results in the increase of the energy barrier for the rotation. The sensitivity of the Nhead-H rotation to the number of surrounding nitrate anions, in conjunction with the varying number of nitrate anions, gives rise to a broad distribution of Nhead-H reorientation times. Our results suggest that the asymmetry of the cations and the larger excluded volume for longer cationic chain are important for both the structural heterogeneity and the dynamical heterogeneities. The observed dynamical heterogeneities may affect the rates of chemical reactions depending on where the reactants are solvated in ionic liquids and provide an additional guideline for the design of RTILs as solvents. © 2018 Author(s).

Molecular Dynamics (MD) is a widely used tool for simulations of particle systems with pair-wise interactions. Since large scale MD simulations are very demanding in computation time, parallelisation is an important factor. As in the current HPC environment different heterogeneous computing architectures are emerging, a benchmark tool for a representative number of these architectures is desirable. OpenCL as a platform-overarching standard provides the capabilities for such a benchmark. This paper describes the implementation of an OpenCL MD benchmark code and discusses the results achieved on different types of computing hardware. © Springer International Publishing AG, part of Springer Nature 2018.

Resistive switching devices emerged a huge amount of interest as promising candidates for non-volatile memories as well as artificial synapses due to their memristive behavior. The main physical and chemical phenomena which define their functionality are driven by externally applied voltages and the resulting electric fields. Although molecular dynamics simulations are widely used in order to describe the dynamics on the corresponding atomic length and time scales, there is a lack of models which allow for the actual driving force of the dynamics, i.e., externally applied electric fields. This is due to the restriction of currently applied models to solely conductive, non-reactive, or insulating materials, with thicknesses on the order of the potential cutoff radius, i.e., 10 Å. In this work, we propose a generic model, which can be applied in particular to describe the resistive switching phenomena of metal-insulator-metal systems. It has been shown that the calculated electric field and force distribution in case of the chosen example system Cu/a-SiO2/Cu are in agreement with the fundamental field theoretical expectations. © 2018 Author(s).

Ab initio molecular dynamics (AIMD) simulations enable the accurate description of reactive molecule-surface scattering especially if energy transfer involving surface phonons is important. However, presently, the computational expense of AIMD rules out its application to systems where reaction probabilities are smaller than about 1%. Here we show that this problem can be overcome by a high-dimensional neural network fit of the molecule-surface interaction potential, which also incorporates the dependence on phonons by taking into account all degrees of freedom of the surface explicitly. As shown for N2 + Ru(0001), which is a prototypical case for highly activated dissociative chemisorption, the method allows an accurate description of the coupling of molecular and surface atom motion and accurately accounts for vibrational properties of the employed slab model of Ru(0001). The neural network potential allows reaction probabilities as low as 10-5 to be computed, showing good agreement with experimental results. © 2017 American Chemical Society.

Solid-liquid interfaces play an important role in many fields like electrochemistry, corrosion, and heterogeneous catalysis. For understanding the related processes, detailed insights into the elementary steps at the atomic level are mandatory. Here we unravel the properties of prototypical surface-defects like adatoms and vacancies at a number of copper-water interfaces including the low-index Cu(111), Cu(100), and Cu(110), as well as the stepped Cu(211) and Cu(311) surfaces. Using a first-principles quality neural network potential constructed from density functional theory reference data in combination with molecular dynamics and metadynamics simulations, we investigate the defect diffusion mechanisms and the associated free energy barriers. Further, the solvent structure and the mobility of the interfacial water molecules close to the defects are analyzed and compared to the defect-free surfaces. We find that, like at the copper-vacuum interface, hopping mechanisms are preferred compared to exchange mechanisms, while the associated barriers for hopping are reduced in the presence of liquid water. The water structure close to adatoms and vacancies exhibits pronounced local features and differs strongly from the structure at the ideal low-index surfaces. Moreover, in particular at Cu(111) the adatoms are very mobile and hopping events along the surface are more frequent than the exchange of coordinating water molecules in their local environment. Consequently, adatom self-diffusion processes at Cu(111) involve entities of adatoms and their associated solvation shells. © 2017 American Chemical Society.

Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for vibrational anharmonic and dynamical effects-typically neglected by conventional quantum chemistry approaches-we base our machine learning strategy on ab initio molecular dynamics simulations. While these simulations are usually extremely time consuming even for small molecules, we overcome these limitations by leveraging the power of a variety of machine learning techniques, not only accelerating simulations by several orders of magnitude, but also greatly extending the size of systems that can be treated. To this end, we develop a molecular dipole moment model based on environment dependent neural network charges and combine it with the neural network potential approach of Behler and Parrinello. Contrary to the prevalent big data philosophy, we are able to obtain very accurate machine learning models for the prediction of infrared spectra based on only a few hundreds of electronic structure reference points. This is made possible through the use of molecular forces during neural network potential training and the introduction of a fully automated sampling scheme. We demonstrate the power of our machine learning approach by applying it to model the infrared spectra of a methanol molecule, n-alkanes containing up to 200 atoms and the protonated alanine tripeptide, which at the same time represents the first application of machine learning techniques to simulate the dynamics of a peptide. In all of these case studies we find an excellent agreement between the infrared spectra predicted via machine learning models and the respective theoretical and experimental spectra. © 2017 The Royal Society of Chemistry.

The ab initio molecular dynamics simulations of metallic, charged, and electrochemical systems require, in principle, the inclusion of unequally occupied electronic states. In this contribution, the general approach to work with fixed but arbitrary occupations within the Car-Parrinello molecular dynamics scheme is revisited, focusing on the procedure which is required to maintain the orthonormality constraints in the commonly used position-Verlet integrator. Expressions to constrain also the orbital velocities, as it is demanded by a velocity-Verlet integrator, are then derived. The generalized unequal-occupation SHAKE algorithm is compared with the standard procedure for damped dynamics (energy optimization) of systems including fully unoccupied electronic states. In turn, the proposed unequal-occupation RATTLE algorithm is validated by the corresponding microcanonical ensemble simulations. It is shown that only with the proper orthogonalization method, a correct ordering of states and energy conserving dynamics can be achieved. © 2017 Author(s).

We present a computational multiscale study of a metal-organic framework (MOF)/polymer composite combining micro- and mesoscopic resolution, by coupling atomistic and coarse grained (CG) force field-based molecular dynamics simulations. As a proof of concept, we describe the copper paddlewheel-based HKUST-1 MOF/poly(vinyl alcohol) composite. Our newly developed CG model reproduces the salient features of the interface in excellent agreement with the atomistic model and allows the investigation of substantially larger systems. The polymer penetrates into the open pores of the MOF as a result of the interactions between its OH groups and the O and Cu atoms in the pores, suggesting an excellent MOF/polymer compatibility. Polymer structure is affected by the MOF surface up to a distance of ∼2.4 times its radius of gyration. This study paves the way toward understanding important interfacial phenomena such as aggregation and phase separation in these mixed matrix systems. © 2017 American Chemical Society.

Effect of small molecules, as they penetrate into a polymer system, is investigated via molecular dynamics simulations. It is found that small spherical particles reduce the glass transition temperature and thus introduce a softening of the material. Results are compared to experimental findings for the effect of different types of small molecules such as water, acetone and ethanol on the glass transition temperature of a polyurethane-based shape memory polymer. Despite the simplicity of the simulated model, MD results are found to be in good qualitative agreement with experimental data. © 2017 The Authors. Published by Elsevier B.V.

We developed an expression for the calculation of the sum frequency generation spectra (SFG) of water interfaces that is based on the projection of the atomic velocities on the local normal modes. Our approach permits one to obtain the SFG signal from suitable velocity-velocity correlation functions, reducing the computational cost to that of the accumulation of a molecular dynamics trajectory, and therefore cutting the overhead costs associated with the explicit calculation of the dipole moment and polarizability tensor. Our method permits to interpret the peaks in the spectrum in terms of local modes, also including the bending region. The results for the water-air interface, obtained using ab initio molecular dynamics simulations, are discussed in connection to recent phase resolved experimental data. © 2017 American Chemical Society.

The elastic properties of crystalline metals scale with their valence electron density. Similar observations have been made for metallic glasses. However, for metallic glasses where covalent bonding predominates, such as metalloid metallic glasses, this relationship appears to break down. At present, the reasons for this are not understood. Using high energy x-ray diffraction analysis of melt spun and thin film metallic glasses combined with density functional theory based molecular dynamics simulations, we show that the physical origin of the ultrahigh stiffness in both metalloid and non-metalloid metallic glasses is best understood in terms of the bond energy density. Using the bond energy density as novel materials design criterion for ultra-stiff metallic glasses, we are able to predict a Co33.0Ta3.5B63.5 short range ordered material by density functional theory based molecular dynamics simulations with a high bond energy density of 0.94 eV Å-3 and a bulk modulus of 263 GPa, which is 17% greater than the stiffest Co-B based metallic glasses reported in literature. © 2017 IOP Publishing Ltd.

Reliable and predictive relationships between fundamental microstructural material properties and observable macroscopic mechanical behaviour are needed for the successful design of new materials. In this study we establish a link between physical properties that are defined on the atomic level and the deformation mechanisms of slip planes and interfaces that govern the mechanical behaviour of a metallic material. To accomplish this, the shear instability energy Γ is introduced, which can be determined via quantum mechanical ab initio calculations or other atomistic methods. The concept is based on a multilayer generalised stacking fault energy calculation and can be applied to distinguish the different shear deformation mechanisms occurring at TiAl interfaces during finite-temperature molecular dynamics simulations. We use the new parameter Γ to construct a deformation mechanism map for different interfaces occurring in this intermetallic. Furthermore, Γ can be used to convert the results of ab initio density functional theory calculations into those obtained with an embedded atom method type potential for TiAl. We propose to include this new physical parameter into material databases to apply it for the design of materials and microstructures, which so far mainly relies on single-crystal values for the unstable and stable stacking fault energy. © 2017 IOP Publishing Ltd.

Modern simulation techniques have reached a level of maturity which allows a wide range of problems in chemistry and materials science to be addressed. Unfortunately, the application of first principles methods with predictive power is still limited to rather small systems, and despite the rapid evolution of computer hardware no fundamental change in this situation can be expected. Consequently, the development of more efficient but equally reliable atomistic potentials to reach an atomic level understanding of complex systems has received considerable attention in recent years. A promising new development has been the introduction of machine learning (ML) methods to describe the atomic interactions. Once trained with electronic structure data, ML potentials can accelerate computer simulations by several orders of magnitude, while preserving quantum mechanical accuracy. This Review considers the methodology of an important class of ML potentials that employs artificial neural networks. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

We report the potential-dependent interactions of trimesic acid with Cu surfaces in EtOH. CV experiments and electrochemical surface-enhanced Raman spectroscopy show the presence of an adsorbed trimesic acid layer on Cu at potentials lower than 0 V vs Cu. The BTC coverage increases as the potential increases, reaching a maximum at 0 V. Based on molecular dynamics simulations, we report adsorption geometries and possible structures of the organic adlayer. We find that, depending on the crystal facet, trimesic acid adsorbs either flat or with one or two of the carboxyl groups facing the metal surface. At higher coverages, a multi-layer forms that is composed mostly of flat-lying trimesic acid molecules. Increasing the potential beyond 0 V activates the Cu-adsorbate interface in such a way that under oxidation of Cu to Cu2 +, a 3-D metal-organic framework forms directly on the electrode surface. © 2017 Elsevier B.V.

We investigate the conformational properties of polymers in ionic microgels in the presence of salt ions by molecular dynamics simulations and analytical theory. A microgel particle consists of coarse-grained linear polymers, which are tetra-functionally crosslinked. Counterions and salt ions are taken into account explicitly, and charge-charge interactions are described by the Coulomb potential. By varying the charge interaction strength and salt concentration, we characterize the swelling of the polyelectrolytes and the charge distribution. In particular, we determine the amount of trapped mobile charges inside the microgel and the Debye screening length. Moreover, we analyze the polymer extension theoretically in terms of the tension blob model taking into account counterions and salt ions implicitly by the Debye-Hückel model. Our studies reveal a strong dependence of the amount of ions absorbed in the interior of the microgel on the electrostatic interaction strength, which is related to the degree of the gel swelling. This implies a dependence of the inverse Debye screening length k on the ion concentration; we find a power-law increase of k with the Coulomb interaction strength with the exponent 3/5 for a salt-free microgel and an exponent 1/2 for moderate salt concentrations. Additionally, the radial dependence of polymer conformations and ion distributions is addressed. © 2017 by the authors.

Ligand exchange plays an important role for organic and inorganic chemical reactions. We demonstrate the existence of a novel water exchange mechanism, the "proton transfer pathway" (PTP), around Na+(aq) in basic (high pH) solution, using reactive molecular dynamics simulations employing a high-dimensional neural network potential. An aqua ligand in the first solvation (hydration) shell around a sodium ion is only very weakly acidic, but if a hydroxide ion is present in the second solvation shell, thermal fluctuations can cause the aqua ligand to transfer a proton to the neighboring OH-, resulting in a transient direct-contact ion pair, Na+-OH-, which is only weakly bound and easily dissociates. The extent to which water exchange events follow the PTP is pH-dependent: in dilute NaOH(aq) solutions, only very few exchanges occur, whereas in saturated NaOH(aq) solutions up to a third of water self-exchange events are induced by proton transfer. The principles and results outlined here are expected to be relevant for chemical synthesis involving bases and alkali metal cations. © 2017 American Chemical Society.

The dissociation of water is an important step in many chemical processes at solid surfaces. In particular, water often spontaneously dissociates near metal oxide surfaces, resulting in a mixture of H2O, H+, and OH- at the interface. Ubiquitous proton-transfer (PT) reactions cause these species to dynamically interconvert, but the underlying mechanisms are poorly understood. Here, we develop and use a reactive high-dimensional neural-network potential based on density functional theory data to elucidate the structural and dynamical properties of the interfacial species at the liquid-water-metal-oxide interface, using the nonpolar ZnO(101̅0) surface as a prototypical case. Molecular dynamics simulations reveal that water dissociation and recombination proceed via two types of PT reactions: (i) to and from surface oxide and hydroxide anions (“surface-PT”) and (ii) to and from neighboring adsorbed hydroxide ions and water molecules (“adlayer-PT”). We find that the adlayer-PT rate is significantly higher than the surface-PT rate. Water dissociation is, for both types of PT, governed by a predominant presolvation mechanism, i.e., thermal fluctuations that cause the adsorbed water molecules to occasionally accept a hydrogen bond, resulting in a decreased PT barrier and an increased dissociation rate as compared to when no hydrogen bond is present. Consequently, we are able to show that hydrogen bond fluctuations govern PT events at the water-metal-oxide interface in a way similar to that in acidic and basic aqueous bulk solutions. © 2017 American Chemical Society.

Nanophase segregation of a bicomponent thiol self-assembled monolayer is predicted using atomistic molecular dynamics simulations and experimentally confirmed. The simulations suggest the formation of domains rich in acid-terminated chains, on one hand, and of domains rich in amide-functionalized ethylene glycol oligomers, on the other hand. In particular, within the amide-ethylene glycol oligomers region, a key role is played by the formation of interchain hydrogen bonds. The predicted phase segregation is experimentally confirmed by the synthesis of 35 and 15 nm gold nanoparticles functionalized with several binary mixtures of ligands. An extensive study by transmission electron microscopy and electron tomography, using silica selective heterogeneous nucleation on acid-rich domains to provide electron contrast, supports simulations and highlights patchy nanoparticles with a trend toward Janus nano-objects depending on the nature of the ligands and the particle size. These results validate our computational platform as an effective tool to predict nanophase separation in organic mixtures on a surface and drive further exploration of advanced nanoparticle functionalization. © 2017 American Chemical Society.

Structural phase transformation and dislocation slip are two important deformation modes of monocrystalline silicon. In the present work, we elucidate mechanisms of inhomogeneous elastic-plastic transition in spherical nanoindentation of monocrystalline silicon by means of molecular dynamics simulations. The Stillinger-Weber potential is utilized to present simultaneous phase transformations and dislocation activities in the silicon nanoindentation. And a bond angle analysis-based method is proposed to quantitatively clarify silicon phases. The influence of crystallographic orientation on the silicon nanoindentation is further addressed. Our simulation results indicate that prior to the “Pop-In” event, Si(0 1 0) undergoes inelastic deformation accompanied by the phase transformation from the Si-I to the Si-III/Si-XII, which is not occurred in Si(1 1 0) and Si(1 1 1). While the phase transformation from the Si-I to the bct-5 is the dominant mechanism of incipient plasticity for each crystallographic orientation, dislocation nucleation is also an operating deformation mode in the elastic-plastic transition of Si(0 1 0). Furthermore, interactions between phase transformations and dislocations are more pronounced in Si(0 1 0) than the other two crystallographic orientations. © 2017 Elsevier B.V.

Sodium hydroxide, NaOH, is one of the most widely-used chemical reagents, but the structural properties of its aqueous solutions have only sparingly been characterized. Here, we automatically classify the cation coordination polyhedra obtained from molecular dynamics simulations. We find that, for example, with increasing concentration, octahedral coordination geometries become less favored, while the opposite is true for the trigonal prism. At high concentrations, the coordination polyhedra frequently deviate considerably from "ideal" polyhedra, because of an increased extent of interligand hydrogen-bonding, in which hydrogen bonds between two ligands, either OH2 or OH-, around the same Na+ are formed. In saturated solutions, with concentrations of about 19 mol L-1, ligands are frequently shared between multiple Na+ ions as a result of the deficiency of solvent molecules. This results in more complex structural patterns involving certain "characteristic" polyhedron connectivities, such as octahedra sharing ligands with capped trigonal prisms, and tetrahedra sharing ligands with trigonal bipyramids. The simulations were performed using a density-functional-theory-based reactive high-dimensional neural network potential, that was extensively validated against available neutron and X-ray diffraction data from the literature. © the Owner Societies 2017.

One of the most prominent consequences of the quantum nature of light atomic nuclei is that their kinetic energy does not follow a Maxwell-Boltzmann distribution. Deep inelastic neutron scattering (DINS) experiments can measure this effect. Thus, the nuclear quantum kinetic energy can be probed directly in both ordered and disordered samples. However, the relation between the quantum kinetic energy and the atomic environment is a very indirect one, and cross-validation with theoretical modeling is therefore urgently needed. Here, we use state of the art path integral molecular dynamics techniques to compute the kinetic energy of hydrogen and oxygen nuclei in liquid, solid, and gas-phase water close to the triple point, comparing three different interatomic potentials and validating our results against equilibrium isotope fractionation measurements. We will then show how accurate simulations can draw a link between extremely precise fractionation experiments and DINS, therefore establishing a reliable benchmark for future measurements and providing key insights to increase further the accuracy of interatomic potentials for water. © 2016 American Chemical Society.

The interfaces in lamellar TiAl alloys have a strong influence on the strength and deformability of the microstructure. It is widely accepted that their number and spacing can be used to tune these properties. However, the results of molecular dynamics simulations of sliding at γ/γ interfaces in lamellar TiAl alloys presented here suggest that important factors, namely the sequence of different interface types as well as the orientation of in-plane directions with respect to the loading axis, have to be included into meso-scale models. Simulations of bicrystal shear show significant differences in the deformation behavior of the different interfaces, as well as pronounced in-plane anisotropy of the shear strength of the individual interfaces. The critical stresses derived from bicrystal shear simulations are of the same order of magnitude as the one for nucleation and motion of twins in a γ-single crystal, showing that these mechanisms are competitive. In total four different deformation mechanisms, interface migration, twin nucleation and migration, dislocation nucleation, and rigid grain boundary sliding are observed. Their occurrence can be understood based on a multilayer generalized stacking fault energy analysis. This link between physical properties, geometry and deformation mechanism can provide guidelines for future alloy development. © 2016 Published by Elsevier Ltd on behalf of Acta Materialia Inc.

The precise description of quantum nuclear fluctuations in atomistic modelling is possible by employing path integral techniques, which involve a considerable computational overhead due to the need of simulating multiple replicas of the system. Many approaches have been suggested to reduce the required number of replicas. Among these, high-order factorizations of the Boltzmann operator are particularly attractive for high-precision and low-temperature scenarios. Unfortunately, to date, several technical challenges have prevented a widespread use of these approaches to study the nuclear quantum effects in condensed-phase systems. Here we introduce an inexpensive molecular dynamics scheme that overcomes these limitations, thus making it possible to exploit the improved convergence of high-order path integrals without having to sacrifice the stability, convenience, and flexibility of conventional second-order techniques. The capabilities of the method are demonstrated by simulations of liquid water and ice, as described by a neural-network potential fitted to the dispersion-corrected hybrid density functional theory calculations. © 2016 Author(s).

Understanding the molecular mechanisms which nature uses to control biomineral growth is a fundamental science goal with profound medical implication. In the case of calcium oxalate, a microscopic understanding of the interactions which regulate the growth and stabilization of metastable phases would permit to inhibit the growth of the crystals which are the main components of kidney stones. Here we use ab initio molecular dynamics simulations to unravel how specific molecular interactions occurring on calcium oxalate dihydrate surface can promote an anisotropic crystal growth. We find that the calcium oxalate dihydrate (100) and (101) surfaces are both hydrophilic and solvated by a strongly bound layer of water; however, they exhibit important differences in their ability to bind water and small molecules such as acetate. In particular, on the (100) surface, the more exposed Ca2+ ions can more strongly bind to negatively charged groups, exerting a protecting action on the surface and preventing its further growth. This mechanism in turn would favor an anisotropic growth of the calcium oxalate dihydrate crystals in the [100] direction, as observed in experiments. © 2016 American Chemical Society.

Acidity of silanol sites at the crystalline quartz/aqueous electrolyte (NaCl, NaI, KCl) interfaces are calculated from ab initio molecular dynamics simulations. pKa's are found to follow a combination of the cationic and anionic Hofmeister series in the order pKa(neat solution) < pKa(NaCl) < pKa(NaI) < pKa(KCl), in agreement with experimental measurements. Rationalization of this ranking is achieved in terms of the microscopic local solvation of the protonated silanols and their conjugated bases, the silanolates SiO-. The change in the pKa is the result of both water destructuring by alkali halides, as well as of the specific cation/SiO- interaction, depending on the electrolyte. Molecular modeling at the atomistic level is required to achieve such comprehension, with ab initio molecular dynamics being able to model complex inhomogeneous charged interfaces and the associated interfacial chemical reactivity. © 2016 American Chemical Society.

Solid-liquid interfaces have received considerable attention in recent years due to their central role in many technologically relevant fields like electrochemistry, heterogeneous catalysis and corrosion. As the chemical processes in these examples take place primarily at the interface, understanding the structural and dynamical properties of the interfacial water molecules is of vital importance. Here, we use a first-principles quality high-dimensional neural network potential built from dispersion-corrected density functional theory data in molecular dynamics simulations to investigate water-copper interfaces as a prototypical case. After performing convergence tests concerning the required supercell size and water film diameter, we investigate numerous properties of the interfacial water molecules at the low-index copper (111), (100) and (110) surfaces. These include density profiles, hydrogen bond properties, lateral mean squared displacements and residence times of the water molecules at the surface. We find that in general the copper-water interaction is rather weak with the strongest interactions observed at the Cu(110) surface, followed by the Cu(100) and Cu(111) surfaces. The distribution of the water molecules in the first hydration layer exhibits a double peak structure. In all cases, the molecules closest to the surface are predominantly allocated on top of the metal sites and are aligned nearly parallel with the oxygen pointing slightly to the surface. The more distant molecules in the first hydration layer at the Cu(111) and Cu(100) surfaces are mainly found in between the top sites, whereas at the Cu(110) surface most of these water molecules are found above the trenches of the close packed atom rows at the surface. © 2016 the Owner Societies.

At the water-air interface, the hydrogen-bond network of water molecules is interrupted, and accordingly, the structure and dynamics of the interfacial water molecules are altered considerably compared with the bulk. Such interfacial water molecules have been studied by surface-specific vibrational sum-frequency generation (SFG) spectroscopy probing high-frequency O-H stretch and H-O-H bending modes. In contrast, the low-frequency librational mode has been much less studied with SFG. Because this mode is sensitive to the hydrogen-bond connectivity, understanding the librational mode of the interfacial water is crucial for unveiling a microscopic view of the interfacial water. Here, we compute the SFG librational mode spectra at the water-air interface by using molecular dynamics simulation. We show that the modeling of the polarizability has a drastic effect on the simulated librational mode spectra, whereas the spectra are less sensitive to the force field models and the modeling of the dipole moment. The simulated librational spectra display a peak centered at ∼700 cm-1, which is close to the infrared peak frequency of the liquid water librational mode of 670 cm-1. This indicates that the librational mode of the interfacial water at the water-air interface closely resembles that of bulk liquid water. © 2016 American Chemical Society.

The temperature-responsive behavior of functionalized metal-organic frameworks (fu-MOF) with the general formula [Zn2(fu-L)2dabco]n has been investigated using molecular dynamics simulations (fu-L = alkoxy-functionalized 1,4-benzenedicarboxylate, dabco = 1,4-diazabicyclo[2.2.2]octane). The studied frameworks show a narrow pore (np) form at low temperatures, while at higher temperatures, large pore (lp) structures can be observed. The transition temperature is controlled by the chemical nature of the linker's side chains as well as their length. In general, enhancing the side chain length decreases the transition temperature. On the other hand, more polar linkers shift the transition temperature to higher values. The so-called opening process of the narrow pores is caused by the thermally induced motion of the alkoxy side chains of the functionalized linkers. For qualitative comparison, the difference in internal energy as well as entropy between two forms (np and lp) was calculated for all studied linker types. (Figure Presented). © 2016 American Chemical Society.

We present a semi-empirical effective Hamiltonian to capture effects of disorder associated with Ba and Sr cations occupying A sites in (BaxSr1-x)TiO3 on its ferroelectric phase transition. Averaging between the parameters of firstprinciples effective Hamiltonians of end members BaTiO3 and SrTiO3, we include a term with an empirical parameter to capture the local polarization and strains arising from the difference between ionic radii of Ba and Sr. Using mixed-space molecular dynamics of the effective Hamiltonian, we determine T-dependent ferroelectric phase transitions in (BaxSr1-x)TiO3 which are in good agreement with experiment. Our scheme of determination of semi-empirical parameters in effective Hamiltonian should be applicable to other perovskite-type ferroelectric solid solutions. ©2016 The Physical Society of Japan.

Atomistic simulations were performed in order to investigated the effect of pore dimension on the interaction of guest molecules with the inner surface of metal-organic frameworks (MOFs). In these systems, which only differ in the metric of their open structure, the chemical nature is conserved, and less impact on the host-guest interaction is expected compared to chemically funcionalized MOFs. However, by performing molecular dynamics simulations of benzene loaded MOF-5 derivatives (IRMOFs), which differ just in the length of the organic linker, it can be shown that impacts are present. The influence of the soft-modification can be explained only by a detailed analysis of the free energy topology and the diffusion mechanism. Note that the calculated self-diffusivity of benzene Dself shows no change with respect to the elongation of the linkers. The apparent contradiction between the macroscopic observable Dself and the microscopic free energy landscape could be resolved by introducing a hopping model for the diffusion process and subsequent Monte Carlo simulations. This study demonstrates the importance of atomistic simulations and the need to understand the host-guest interaction in MOFs in a multiscale fashion. © 2016 American Chemical Society.

We propose a new force field for trimethylamine N-oxide (TMAO), which is designed to reproduce the long-lived and highly directional hydrogen bond between the TMAO oxygen (OTMAO) atom and surrounding water molecules. Based on the data obtained by ab initio molecular dynamics simulations, we introduce three dummy sites around OTMAO to mimic the OTMAO lone pairs and we migrate the negative charge on the OTMAO to the dummy sites. The force field model developed here improves both structural and dynamical properties of aqueous TMAO solutions. Moreover, it reproduces the experimentally observed dependence of viscosity upon increasing TMAO concentration quantitatively. The simple procedure of the force field construction makes it easy to implement in molecular dynamics simulation packages and makes it compatible with the existing biomolecular force fields. This paves the path for further investigation of protein-TMAO interaction in aqueous solutions. © 2016 Author(s).

A multiscale simulation approach based on atomistic calculations and a discrete diffusion model is developed and applied to carbon-supersaturated ferrite, as experimentally observed in severely deformed pearlitic steel. We employ the embedded atom method and the nudged elastic band technique to determine the energetic profile of a carbon atom around a screw dislocation in bcc iron. The results clearly indicate a special region in the proximity of the dislocation core where C atoms are strongly bound, but where they can nevertheless diffuse easily due to low barriers. Our analysis suggests that the previously proposed pipe mechanism for the case of a screw dislocation is unlikely. Instead, our atomistic as well as the diffusion model results support the so-called drag mechanism, by which a mobile screw dislocation is able to transport C atoms along its glide plane. Combining the C-dislocation interaction energies with density-functional-theory calculations of the strain dependent C formation energy allows us to investigate the C supersaturation of the ferrite phase under wire drawing conditions. Corresponding results for local and total C concentrations agree well with previous atom probe tomography measurements indicating that a significant contribution to the supersaturation during wire drawing is due to dislocations. © 2016 Acta Materialia Inc.

We study the impact of lattice vibrations on magnetic and electronic properties of paramagnetic bcc and fcc iron at finite temperature, employing the disordered local moments molecular dynamics (DLM-MD) method. Vibrations strongly affect the distribution of local magnetic moments at finite temperature, which in turn correlates with the local atomic volumes. Without the explicit consideration of atomic vibrations, the mean local magnetic moment and mean field derived magnetic entropy of paramagnetic bcc Fe are larger compared to paramagnetic fcc Fe, which would indicate that the magnetic contribution stabilizes the bcc phase at high temperatures. In the present study we show that this assumption is not valid when the coupling between vibrations and magnetism is taken into account. At the γ-δ transition temperature (1662 K), the lattice distortions cause very similar magnetic moments of both bcc and fcc structures and hence magnetic entropy contributions. This finding can be traced back to the electronic densities of states, which also become increasingly similar between bcc and fcc Fe with increasing temperature. Given the sensitive interplay of the different physical excitation mechanisms, our results illustrate the need for an explicit consideration of vibrational disorder and its impact on electronic and magnetic properties to understand paramagnetic Fe. Furthermore, they suggest that at the γ-δ transition temperature electronic and magnetic contributions to the Gibbs free energy are extremely similar in bcc and fcc Fe. © 2016 American Physical Society.

Directly manipulating and controlling the size and shape of metal nanoparticles is a key step for their tailored applications. In this work, molecular dynamics simulations were applied to understand the microscopic origin of the asymmetric growth mechanism in gold nanorods. Different factors influencing the growth were selectively included in the models to unravel the role of the surfactants and ions. In the early stage of the growth, when the seed is only a few nanometers large, a dramatic symmetry breaking occurs as the surfactant layer preferentially covers the (100) and (110) facets, leaving the (111) facets unprotected. This anisotropic surfactant layer in turn promotes anisotropic growth with the less protected tips growing faster. When silver salt is added to the growth solution, the asymmetry of the facets is preserved, but the Br−concentration at the interface increases, resulting in increased surface passivation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Proton transfer processes play an important role in many fields of chemistry. In dilute basic aqueous solutions, proton transfer from water molecules to hydroxide ions is aided by "presolvation", i.e., thermal fluctuations that modify the hydrogen-bonding environment around the proton-receiving OH- ion to become more similar to that of a neutral H2O molecule. In particular at high concentrations, however, the underlying mechanisms and especially the role of the counterions are little understood. As a prototypical case, we investigate aqueous NaOH solutions using molecular dynamics simulations employing a reactive high-dimensional neural-network potential constructed from density functional theory reference data. We find that with increasing concentration the predominant proton transfer mechanism changes from being "acceptor-driven", i.e., governed by the presolvation of OH-, to "donor-driven", i.e., governed by the presolvation of H2O, and back to acceptor-driven near the room-temperature solubility limit of 19 mol/L, which corresponds to an extremely solvent-deficient system containing only about one H2O molecule per ion. Specifically, we identify concentration ranges where the proton transfer rate is mostly affected by OH- losing an accepted hydrogen bond, OH- forming a donated hydrogen bond, H2O forming an accepted hydrogen bond, or H2O losing a coordinated Na+. Presolvation also manifests itself in the shortening of the Na+-OH2 distances, in that the Na+ "pushes" one of the H2O protons away. © 2016 American Chemical Society.

Chitin is one of the most abundant structural biomolecules in nature, where it occurs in the form of nanofibrils that are the smallest building blocks for many biological structural materials, such as the exoskeleton of Arthropoda. Despite this fact, little is known about the structural properties of these nanofibrils. Here, we present a theoretical study of a single chitin molecule and 10 alpha-chitin nanofibrils with different numbers of chains in an aqueous environment that mimics the conditions in natural systems during self-assembly. Our extensive analysis of the molecular dynamics trajectories, including free energy calculations for every model system, reveals not only the structural properties of the nanofibrils, but also provides insight into the principles of nanofibril formation. We identified the fundamental phenomena occurring in the chitin nanofibrils such as their hydrogen bonding pattern and resulting helical shape. With increasing size, the nanofibrils become increasingly stable and their structural properties approach those of crystalline alpha-chitin if they consist of more than 20 chains. Interestingly, this coincides with the typical size of chitin nanofibrils observed in natural systems, suggesting that their evolutionary success was at least partially driven by these specific structure-property relations.

A new adaptive resolution technique for particle-based multi-level simulations of fluids is presented. In the approach, the representation of fluid and solvent particles is changed on the fly between an atomistic and a coarse-grained description. The present approach is based on a hybrid coupling of the multiparticle collision dynamics (MPC) method and molecular dynamics (MD), thereby coupling stochastic and deterministic particle-based methods. Hydrodynamics is examined by calculating velocity and current correlation functions for various mixed and coupled systems. We demonstrate that hydrodynamic properties of the mixed fluid are conserved by a suitable coupling of the two particle methods, and that the simulation results agree well with theoretical expectations. © 2016 Elsevier Inc.

Phase change memories rest on the ability of some chalcogenide alloys to undergo a fast and reversible transition between the crystalline and amorphous phases upon Joule heating. The fast crystallization is due to a high nucleation rate and a large crystal growth velocity which are actually possible thanks to the fragility of the supercooled liquid that allows for the persistence of a high atomic mobility at high supercooling where the thermodynamical driving force for crystallization is also high. Since crystallization in the devices occurs by rapidly heating the amorphous phase, hysteretic effects might arise with a different diffusion coefficient and viscosity on heating than on cooling. In this work, we have quantified these hysteretic effects in the phase change compound GeTe by means of molecular dynamics simulations. The atomic mobility in the overheated amorphous phase is lower than in supercooled liquid at the same temperature and the viscosity is consequently higher. Still, the simulations of the overheated amorphous phase reveal a breakdown of the Stokes-Einstein relation between the diffusion coefficient and the viscosity, similarly to what we found previously in the supercooled liquid. Evidences are provided that the breakdown is due to the emergence of dynamical heterogeneities at high supercooling. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Whereas the interactions between water molecules are dominated by strongly directional hydrogen bonds (HBs), it was recently proposed that relatively weak, isotropic van der Waals (vdW) forces are essential for understanding the properties of liquid water and ice. This insight was derived from ab initio computer simulations, which provide an unbiased description of water at the atomic level and yield information on the underlying molecular forces. However, the high computational cost of such simulations prevents the systematic investigation of the influence of vdW forces on the thermodynamic anomalies of water. Here, we develop efficient ab initio-quality neural network potentials and use them to demonstrate that vdW interactions are crucial for the formation of water's density maximum and its negative volume of melting. Both phenomena can be explained by the flexibility of the HB network, which is the result of a delicate balance of weak vdW forces, causing, e.g., a pronounced expansion of the second solvation shell upon cooling that induces the density maximum.

We followed the collective atomic-scale motion of Na atoms on a vicinal Cu(115) surface within a time scale of pico- to nanoseconds using helium spin echo spectroscopy. The well-defined stepped structure of Cu(115) allows us to study the effect that atomic steps have on the adsorption properties, the rate for motion parallel and perpendicular to the step edge, and the interaction between the Na atoms. With the support of a molecular dynamics simulation we show that the Na atoms perform strongly anisotropic 1D hopping motion parallel to the step edges. Furthermore, we observe that the spatial and temporal correlations between the Na atoms that lead to collective motion are also anisotropic, suggesting the steps efficiently screen the lateral interaction between Na atoms residing on different terraces. © 2015 American Chemical Society.

A lot of progress has been made in recent years in the development of atomistic potentials using machine learning (ML) techniques. In contrast to most conventional potentials, which are based on physical approximations and simplifications to derive an analytic functional relation between the atomic configuration and the potential-energy, ML potentials rely on simple but very flexible mathematical terms without a direct physical meaning. Instead, in case of ML potentials the topology of the potential-energy surface is "learned" by adjusting a number of parameters with the aim to reproduce a set of reference electronic structure data as accurately as possible. Due to this bias-free construction, they are applicable to a wide range of systems without changes in their functional form, and a very high accuracy close to the underlying first-principles data can be obtained. Neural network potentials (NNPs), which have first been proposed about two decades ago, are an important class of ML potentials. Although the first NNPs have been restricted to small molecules with only a few degrees of freedom, they are now applicable to high-dimensional systems containing thousands of atoms, which enables addressing a variety of problems in chemistry, physics, and materials science. In this tutorial review, the basic ideas of NNPs are presented with a special focus on developing NNPs for high-dimensional condensed systems. A recipe for the construction of these potentials is given and remaining limitations of the method are discussed. © 2015 Wiley Periodicals, Inc.

Thermal spray processes are widely used for the manufacture of advanced coating systems, e.g. metallic coatings for wear and corrosion protection. The desired coating properties are closely related to the microstructure, which is highly influenced by the processing parameters, such as temperature, size and velocity of the sprayed particles. In this paper, large scale Molecular Dynamics simulations are conducted to investigate the microstructure formation mechanisms during the spraying process of hot nano-particles onto a substrate at room temperature using pure copper as a benchmark material representing for a wider class of face-centered-cubic metals. To evaluate the influence of processing parameters on the coating morphology, a number of simulations are performed in which the initial temperature, size and velocity of copper particles are systematically varied in order to investigate the thermal and microstructural evolution during impaction. Two distinct types of microstructural formation mechanisms, resulting in different coating morphologies, are observed in the present investigation, which are either governed by plastic deformation or by the process of melting and subsequent solidification. Furthermore, a thermodynamically motivated model as a function of the particle temperature and velocity is developed, which predicts the microstructural mechanisms observed in the simulations. The results provide an elementary insight into the microstructure formation mechanisms on an atomistic scale, which can serve as basic input for continuum modeling of thermal spray process. © 2015 Published by Elsevier B.V.

We present a combined experimental sum-frequency generation (SFG) spectroscopy and ab initio molecular dynamics simulations study to clarify the structure and orientation of water at zwitterionic phosphatidylcholine (PC) lipid and amine N-oxide (AO) surfactant monolayers. Simulated O-H stretch SFG spectra of water show good agreement with the experimental data. The SFG response at the PC interface exhibits positive peaks, whereas both negative and positive bands are present for the similar zwitterionic AO interface. The positive peaks at the water/PC interface are attributed to water interacting with the lipid carbonyl groups, which act as efficient hydrogen bond acceptors. This allows the water hydrogen bond network to reach, with its (up-oriented) O-H groups, into the headgroup of the lipid, a mechanism not available for water underneath the AO surfactant. This highlights the role of the lipid carbonyl group in the interfacial water structure at the membrane interface, namely, stabilizing the water hydrogen bond network. © 2015 American Chemical Society.

The dynamics of adsorbed CO2 in the metal-organic framework Zn2(bdc)2 dabco (DMOF-1) was investigated using molecular dynamics (MD) simulations and 13C NMR spectroscopy. The statistical analysis of the MD trajectories suggest a preferred localization of the CO2 molecules in the Zn2(bdc)4 corners of the DMOF-1 lattice. The adsorbed molecules retain a high but anisotropic rotational and translational mobility in the channel system. Based on these MD-results, the residual chemical shift anisotropy 〈Δδ〉MD = -114 ppm and the diffusion anisotropy (D∥D⊥)MD = 9.8 ± 0.5 were calculated. They are found to be in reasonable agreement with the experimental NMR data of 〈Δδ〉NMR=-(55 ± 2) ppm and (D∥D⊥)NMR = 3 respectively. © 2015 Elsevier Inc. All rights reserved.

Investigating the properties of protons in water is essential for understanding many chemical processes in aqueous solution. While important insights can in principle be gained by accurate and well-established methods like ab initio molecular dynamics simulations, the computational costs of these techniques are often very high. This prevents studying large systems on long time scales, which is severely limiting the applicability of computer simulations to address a wide range of interesting phenomena. Developing more efficient potentials enabling the simulation of water including dissociation and recombination events with first-principles accuracy is a very challenging task. In particular protonated water clusters have become important model systems to assess the reliability of such potentials, as the presence of the excess proton induces substantial changes in the local hydrogen bond patterns and many energetically similar isomers exist, which are extremely difficult to describe. In recent years it has been demonstrated for a number of systems including neutral water clusters of varying size that neural networks (NNs) can be used to construct potentials with close to first-principles accuracy. Based on density-functional theory (DFT) calculations, here we present a reactive full-dimensional NN potential for protonated water clusters up to the octamer. A detailed investigation of this potential shows that the energetic, structural, and vibrational properties are in excellent agreement with DFT results making the NN approach a very promising candidate for developing a high-quality potential for water. This finding is further supported by first preliminary but very encouraging NN-based simulations of the bulk liquid. This journal is © the Owner Societies 2015.

Phase change materials are the active compounds in optical disks and in nonvolatile phase change memory devices. These applications rest on the fast and reversible switching between the amorphous and the crystalline phases, which takes place in the nano domain in both the time and the length scales. The fast crystallization is a key feature for the applications of phase change materials. In this work, we have investigated by means of large scale molecular dynamics simulations the crystal growth of the prototypical phase change compound GeTe at the interface between the crystalline and the supercooled liquid reached in the device upon heating the amorphous phase. A neural network interatomic potential, markedly faster with respect to first-principles methods, allowed us to consider high-symmetry crystalline surfaces as well as polycrystalline models that are very close to the actual geometry of the memory devices. We have found that the crystal growth from the interface is dominant at high temperatures while it is competing with homogeneous crystallization in the melt at lower temperatures. The crystal growth velocity markedly depends on the crystallographic plane exposed at the interface, the (100) surface being kinetically dominant with respect to the (111) surface. Polycrystalline interfaces, representative of realistic conditions in phase change memory devices, grow at significantly slower pace because of the presence of grain boundaries. © 2015 American Chemical Society.

Ab initio molecular dynamics (AIMD) simulations in trimethylamine N-oxide (TMAO)-D2O solution are employed to elucidate the effects of TMAO on the reorientational dynamics of D2O molecules. By decomposing the O-D groups of the D2O molecules into specific subensembles, we reveal that water reorientational dynamics are retarded considerably in the vicinity of the hydrophilic TMAO oxygen (OTMAO) atom, due to the O-D···OTMAO hydrogen-bond. We find that this reorientational motion is governed by two distinct mechanisms: The O-D group rotates (1) after breaking the O-D···OTMAO hydrogen-bond, or (2) together with the TMAO molecule while keeping this hydrogen-bond intact. While the orientational slow-down is prominent in the AIMD simulation, simulations based on force field models exhibit much faster dynamics. The simulated angle-resolved radial distribution functions illustrate that the O-D···OTMAO hydrogen-bond has a strong directionality through the sp3 orbital configuration in the AIMD simulation, and this directionality is not properly accounted for in the force field simulation. These results imply that care must be taken when modeling negatively charged oxygen atoms as single point charges; force field models may not adequately describe the hydration configuration and dynamics. © 2015 American Chemical Society.

In the present work, we investigate the wear mechanisms of a Cu bi-crystal containing a random high angle grain boundary by means of molecular dynamics simulations. The underlying deformation behavior of the material is analyzed and further related to the observed characteristics of mechanical response and resulting morphology of the worn surface. In particular, the grain boundary-associated mechanisms are characterized by advanced analysis techniques for lattice defects. Our simulation results indicate that in addition to dislocation slip and dislocation-grain boundary interactions, grain boundary migration plays an important role in the plastic deformation of Cu bi-crystal. It is found that the wear behavior of Cu depends on the crystallographic orientation of the worn surface and can be altered quite significantly by the presence of a grain boundary. © 2015 Elsevier B.V.

Polycrystalline material generally exhibits degradation in its mechanical properties and shows more tendency for intergranular fracture due to segregation and diffusion of hydrogen on the grain boundaries (GBs). Understanding the parameters affecting the diffusion and binding of hydrogen within GBs will allow enhancing the mechanical properties of the commercial engineering materials and developing interface dominant materials. In practice during forming processes, the coincidence site lattice (CSL) GBs are experiencing deviations from their ideal configurations. Consequently, this will change the atomic structural integrity by superposition of sub-boundary dislocation networks on the ideal CSL interfaces. For this study, the ideal ∑ 3 111 [11 0] GB structure and its angular deviations in BCC iron within the range of Brandon criterion will be studied comprehensively using molecular statics (MS) simulations. The clean GB energy will be quantified, followed by the GB and free surface segregation energies calculations for hydrogen atoms. Rice-Wang model will be used to assess the embrittlement impact variation over the deviation angles. The results showed that the ideal GB structure is having the greatest resistance to embrittlement prior GB hydrogen saturation, while the 3° deviated GB is showing the highest susceptibility to embrittlement. Upon saturation, the 5° deviated GB appears to have the highest resistance instead due to the lowest stability of hydrogen atoms observed in the free surfaces of its simulation cell. Molecular dynamics (MD) simulations are then applied to calculate hydrogen diffusivity within the ideal and deviated GB structure. It is shown that hydrogen diffusivity decreases significantly in the deviated GB models. In addition, the 5° deviated GB is representing the local minimum for diffusivity results suggesting the existence of the highest atomic disorder and excessive secondary dislocation accommodation within this interface. Copyright © 2015 by ASME.

Understanding the microscopic origin of the acid-base behavior of mineral surfaces in contact with water is still a challenging task, for both the experimental and the theoretical communities. Even for a relatively simple material, such as silica, the origin of the bimodal acidity behavior is still a debated topic. In this contribution we calculate the acidity of single sites on the humid silica surface represented by a model for the hydroxylated amorphous surface. Using a thermodynamic integration approach based on ab initio molecular dynamics, we identify two different acidity values. In particular, some convex geminals and some type of vicinals are very acidic (pKa = 2.9 and 2.1, respectively) thanks to a special stabilization of their deprotonated forms. This recalls the behavior of the out-of-plane silanols on the crystalline (0001) α-quartz surface, although the acidity here is even stronger. On the contrary, the concave geminals and the isolated groups present a quite high pKa (8.9 and 10.3, respectively), similar to the one of silicic acid in liquid water. © 2015 American Chemical Society.

We present a flexible and fully adaptive dynamic load-balancing scheme, which is designed for particle simulations of three-dimensional systems with short ranged interactions. The method is based on domain decomposition with non-orthogonal non-convex domains, which are constructed based on a local repartitioning of computational work between neighbouring processors. Domains are dynamically adjusted in a flexible way under the condition that the original topology is not changed, i.e. neighbour relations between domains are retained, which guarantees a fixed communication pattern for each domain during a simulation. Extensions of this scheme are discussed and illustrated with examples, which generalise the communication patterns and do not fully restrict data exchange to direct neighbours. The proposed method relies on a linked cell algorithm, which makes it compatible with existing implementations in particle codes and does not modify the underlying algorithm for calculating the forces between particles. The method has been implemented into the molecular dynamics community code IMD and performance has been measured for various molecular dynamics simulations of systems representing realistic problems from materials science. It is found that the method proves to balance the work between processors in simulations with strongly inhomogeneous and dynamically changing particle distributions, which results in a significant increase of the efficiency of the parallel code compared both to unbalanced simulations and conventional load-balancing strategies. © 2015 Elsevier B.V. All rights reserved.

Porosity switching in the crystalline solid state is a unique phenomenon observed only in a limited number of materials. The switching behavior of two metal-organic frameworks as well as their respective solid solutions of composition [Zn2(BME-bdc)x(DB-bdc)2-xdabco]n (x = 2; 1.5; 1.0; 0.5; 0) is studied in situ during the adsorption of CO2 and Xe using X-ray diffraction and NMR techniques. The diffraction data, measured during the adsorption suggest a direct one-step phase transition (switching) from the narrow pore phase to the large pore phase beyond the transition pressure. An intermediate phase was found only in one compound within a narrow pressure range around the phase transition pressure region. In situ high-pressure 13C NMR spectroscopy of adsorbed CO2 also allowed following the gating behavior of the studied materials by monitoring the signal of adsorbed CO2. The 13C NMR spectra exhibit a pronounced broadening indicating a certain degree of order for the adsorbed molecules inside the pores. This ordering effect and the resulting line broadening depend on the linker functionalization as could be confirmed by corresponding molecular dynamics (MD) simulations. © 2015 Elsevier Inc.

Despite its relevance to industrial, environmental and medical application, the fluorite/water interface still lacks a microscopic/atomistic characterization. In this contribution we provide the first atomistic description of such interface using first principles molecular dynamics simulations. Our models, which explore a wide range of pH, are able to provide a rational of the recent vibrational spectroscopy experiments. In particular we find that at neutral pH the water at the interface is disordered, in agreement with the experimental data, and explaining why no Vibrational Sum Frequency Generation (VSFG) signal is recorded. At high pH, OH groups which localize at the interface are responsible for the “free OH signal” recorded in the vibrational spectroscopy experiments. Finally we propose one possible model for the low pH condition where the F vacancies induce a strong layering of the interfacial water. © Springer International Publishing Switzerland 2015.

The interaction of dislocations with precipitates is an essential strengthening mechanism in metals, as exemplified by the superior high-temperature strength of Ni-base superalloys. Here we use atomistic simulation samples generated from atom probe tomography data of a single crystal superalloy to study the interactions of matrix dislocations with a γ′ precipitate in molecular dynamics simulations. It is shown that the precipitate morphology, in particular its local curvature, and the local chemical composition significantly alter both, the misfit dislocation network which forms at the precipitate interface, and the core structure of the misfit dislocations. Simulated tensile tests reveal the atomic scale details of many experimentally observed dislocation-precipitate interaction mechanisms, which cannot be reproduced by idealized simulation setups with planar interfaces. We thus demonstrate the need to include interface curvature in the study of semicoherent precipitates and introduce as an enabling method atom probe tomography-informed atomistic simulations. © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Phonon dispersion relations and electron-phonon coupling of hole-doped trigonal GeTe have been computed by density functional perturbation theory. This compound is a prototypical phase change material of interest for applications in phase change non-volatile memories. The calculations allowed us to estimate the electron-phonon contribution to the thermal boundary resistance at the interface between the crystalline and amorphous phases present in the device. The lattice contribution to the thermal boundary resistance has been computed by non-equilibrium molecular dynamics simulations with an interatomic potential based on a neural network scheme. We find that the electron-phonon term contributes to the thermal boundary resistance to an extent which is strongly dependent on the concentration and mobility of the holes. Further, for measured values of the holes concentration and electrical conductivity, the electron-phonon term is larger than the contribution from the lattice. It is also shown that the presence of Ge vacancies, responsible for the p-type degenerate character of the semiconductor, strongly affects the lattice thermal conductivity of the crystal. © 2015 AIP Publishing LLC.

Molecular dynamics simulations were performed to investigate dislocation network formations in a coherent twin boundary in Cu. Depending on the activated glide system, the initial flawless twin boundary can be heavily or sparsely decorated by a dislocation network. The dislocation mechanism leading to a heavy dislocation network at the twin boundary and its consequence on mechanical properties will be discussed. © 2015 Acta Materialia Inc.

Using density-functional theory in combination with the direct force method and molecular dynamics we investigate the vibrational properties of a binary Cr-Re σ-phase. In the harmonic approximation, we have computed phonon dispersion curves and density of states, evidencing structural and chemical effects. We found that the σ-phase is mechanically unstable in some configurations, for example, when all crystallographic sites are occupied by Re atoms. By using a molecular-dynamics-based method, we have analysed the anharmonicity in the system and found negligible effects (∼0.5 kJ/mol) on the Helmholtz energy of the binary Cr-Re σ-phase up to 2000 K (∼0.8Tm). Finally, we show that the vibrational contribution has significant consequences on the disordering of the σ-phase at high temperature. © 2014 AIP Publishing LLC.

Advanced solid-state 2D NMR spectroscopy and molecular dynamics computation are employed to investigate the interaction between adsorbed ferrocene molecules and the MOF-5 lattice. Relayed 13C-1H heteronuclear correlation (HETCOR) 2D NMR spectra clearly indicate short-distance contacts between the ferrocene guests and the benzene-1,4-dicarboxylic-acid linkers, mediated via intermolecular 1 H spin diffusion. By use of 2D 1H-1H correlation spectroscopy the distances between 1H nuclei in the guests and the linkers are estimated to be shorter than 0.5 nm. MD computer simulations support the interpretation of the 2D solid state NMR studies. Moreover, they suggest a wide distribution of intermolecular distances in this host-guest system with the shortest intermolecular hydrogen-hydrogen distances of 0.15 nm. © 2013 Elsevier Inc. All rights reserved.

Calcium Silicate Hydrates (C-S-H) are the major hydration products of portland cement paste. The accurate description of acid-base reactions at the surface of C-S-H particles is essential for both understanding the ion sorption equilibrium in cement and prediction of mechanical properties of the hardened cement paste. Ab initio molecular dynamics simulations at the density functional level of theory were applied to calculate intrinsic acidity constants (pK a's) of the relevant -SiOH and -CaOH2 groups on the C-S-H surfaces using a thermodynamic integration technique. Ion sorption equilibrium in C-S-H was modeled applying ab initio calculated pKa's in titrating Grand Canonical Monte Carlo simulations using a coarse-grained model for C-S-H/solution interface in the framework of the Primitive Model for electrolytes. The modeling results were compared with available data from electrophoretic measurements. The model predictions were found to satisfactorily reproduce available experimental data. © 2014 American Chemical Society.

The development of interatomic potentials employing artificial neural networks has seen tremendous progress in recent years. While until recently the applicability of neural network potentials (NNPs) has been restricted to low-dimensional systems, this limitation has now been overcome and high-dimensional NNPs can be used in large-scale molecular dynamics simulations of thousands of atoms. NNPs are constructed by adjusting a set of parameters using data from electronic structure calculations, and in many cases energies and forces can be obtained with very high accuracy. Therefore, NNP-based simulation results are often very close to those gained by a direct application of first-principles methods. In this review, the basic methodology of high-dimensional NNPs will be presented with a special focus on the scope and the remaining limitations of this approach. The development of NNPs requires substantial computational effort as typically thousands of reference calculations are required. Still, if the problem to be studied involves very large systems or long simulation times this overhead is regained quickly. Further, the method is still limited to systems containing about three or four chemical elements due to the rapidly increasing complexity of the configuration space, although many atoms of each species can be present. Due to the ability of NNPs to describe even extremely complex atomic configurations with excellent accuracy irrespective of the nature of the atomic interactions, they represent a general and therefore widely applicable technique, e.g. for addressing problems in materials science, for investigating properties of interfaces, and for studying solvation processes. © 2014 IOP Publishing Ltd.

Lattice defects such as vacancies, voids and dislocations are inevitably present in any material of technological interest. In this work, non-equilibrium molecular dynamics simulations are conducted to investigate how the monatomic vacancies and nanovoids influence the lattice thermal conductivity of silicon. The results show a clear non-linear decrease of the thermal conductivity with increasing defect volume fraction. Furthermore, it is found that for a given volume fraction of defects, a random distribution shows a lower lattice thermal conductivity. To develop a fundamental understanding of these observations, the spectral energy densities for all phonon branches obtained from 2D Fourier transformations of the atomic trajectories are analyzed. This yields the mean phonon group velocities and relaxation times, which are the main physical quantities contributing to the lattice thermal conductivity. Our analysis reveals that the phonon relaxation time is the most important parameter for describing the degrading of the thermal transport behavior in the defected structures. © 2014 IOP Publishing Ltd.

Glass-forming liquids exhibit a rich phenomenology upon confinement. This is often related to the effects arising from wall-fluid interactions. Here we focus on the interesting limit where the separation of the confining walls becomes of the order of a few particle diameters. For a moderately polydisperse, densely packed hard-sphere fluid confined between two smooth hard walls, we show via event-driven molecular dynamics simulations the emergence of a multiple reentrant glass transition scenario upon a variation of the wall separation. Using thermodynamic relations, this reentrant phenomenon is shown to persist also under constant chemical potential. This allows straightforward experimental investigation and opens the way to a variety of applications in micro-and nanotechnology, where channel dimensions are comparable to the size of the contained particles. The results are in line with theoretical predictions obtained by a combination of density functional theory and the mode-coupling theory of the glass transition. © 2014 Macmillan Publishers Limited.

Analytic bond-order potentials (BOPs) for magnetic transition metals are applied for pure iron as described by an orthogonal d-valent tight-binding (TB) model. Explicit analytic equations for the gradients of the binding energy with respect to the Hamiltonian on-site levels are presented, and are then used to minimize the energy with respect to the magnetic moments, which is equivalent to a TB self-consistency scheme. These gradients are also used to calculate the exact forces, consistent with the energy, necessary for efficient relaxations and molecular dynamics. The Jackson kernel is used to remove unphysical negative densities of states, and approximations for the asymptotic recursion coefficients are examined. BOP, TB and density functional theory results are compared for a range of bulk and defect magnetic structures. The BOP energies and magnetic moments for bulk structures are shown to converge with increasing numbers of moments, with nine moments sufficient for a quantitative comparison of structural energy differences. The formation energies of simple defects such as the monovacancies and divacancies also converge rapidly. Other physical quantities, such as the position of the high-spin to low-spin transition in ferromagnetic fcc (face centred cubic) iron, surface peaks in the local density of states, the elastic constants and the formation energies of the self-interstitial atom defects, require higher moments for convergence. © 2014 IOP Publishing Ltd.

Molecular dynamics simulation is used to study the formation of the a 0 〈1 0 0〉 binary dislocation junction in body-centered cubic Fe. Results show that under an applied strain two intersecting 1/2 a 0 〈1 1 1〉 dislocations, one mobile edge and one immobile screw, form an a0 〈1 0 0〉 binary junction of mixed character in the glide plane of the mobile edge dislocation. It appears, however, that the binary junction does not necessarily lay in one of the three possible {1 1 0} glide planes of the screw dislocation. The binary junction starts to unzip as the impinging edge dislocation bows around and moves away, which results in the formation of a screw dipole along its Burgers vector. The dipole eventually annihilates, completing the unzipping process of the junction, which liberates the edge dislocation. The effects of temperature and strain rate on the unzipping of the junction are quantified by the critical release stress needed to detach the edge dislocation from the screw one. The critical stress decreases when the temperature increases from 10 to 300 K, whereas it increases with increasing applied strain rate, or dislocation speed. The interaction mechanism and strength of the a0 〈1 0 0〉 binary junction as an obstacle to the edge dislocation are compared to that of other types of defect, namely nanosized voids, Cu and Cr precipitates, and dislocation loops in Fe. It appears that the binary junction strength is in the lowest range, comparable to that of a coherent Cr precipitate. © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The structural organization of water at a model of amorphous silica-liquid water interface is investigated by ab initio molecular dynamics (AIMD) simulations at room temperature. The amorphous surface is constructed with isolated, H-bonded vicinal and geminal silanols. In the absence of water, the silanols have orientations that depend on the local surface topology (i.e. presence of concave and convex zones). However, in the presence of liquid water, only the strong inter-silanol H-bonds are maintained, whereas the weaker ones are replaced by H-bonds formed with interfacial water molecules. All silanols are found to act as H-bond donors to water. The vicinal silanols are simultaneously found to be H-bond acceptors from water. The geminal pairs are also characterized by the formation of water H-bonded rings, which could provide special pathways for proton transfer(s) at the interface. The first water layer above the surface is overall rather disordered, with three main domains of orientations of the water molecules. We discuss the similarities and differences in the structural organization of the interfacial water layer at the surface of the amorphous silica and at the surface of the crystalline (0 0 0 1) quartz surface. © 2014 IOP Publishing Ltd.

The synthesis of a stereochemically pure concave tribenzotriquinacene receptor (7) for C60 fullerene, possessing C3 point group symmetry, by threefold condensation of C2-symmetric 1,2-diketone synthons (5) and a hexaaminotribenzotriquinacene core (6) is described. The chiral diketone was synthesized in a five-step reaction sequence starting from C2h-symmetric 2,6-di-tert-butylanthracene. The highly diastereo-discriminating Diels-Alder reaction of 2,6-di-tert-butylanthracene with fumaric acid di(-)menthyl ester, catalyzed by aluminium chloride, is the relevant stereochemistry introducing step. The structure of the fullerene receptor was verified by 1H and 13C NMR spectroscopy, mass spectrometry and single crystal X-ray diffraction. VCD and ECD spectra were recorded, which were corroborated by ab initio DFT calculations, establishing the chiral nature of 7 with about 99.7 % ee, based on the ee (99.9 %) of the chiral synthon (1). The absolute configuration of 7 could thus be established as all-S [(2S,7S,16S,21S,30S,35S)-(7)]. Spectroscopic titration experiments reveal that the host forms 1:1 complexes with either pure fullerene (C60) or fullerene derivatives, such as rotor 1'-(4-nitrophenyl)-3'-(4-N,N- dimethylaminophenyl)-pyrazolino[4',5':1,2][60]fullerene (R). The complex stability constants of the complexes dissolved in CHCl3/CS 2 (1:1 vol. %) are K([C60-7])=319(±156) M -1 and K([R-7])=110(±50) M-1. With molecular dynamics simulations using a first-principles parameterized force field the asymmetry of the rotational potential for [R-7] was shown, demonstrating the potential suitability of receptor 7 to act as a stator in a unidirectionally operating nanoratchet. Going through the motions: The synthesis of a stereochemically pure concave tribenzotriquinacene receptor (1) for C 60 fullerenes is described. Spectroscopic titration experiments reveal that the host forms 1:1 complexes with fullerenes. Molecular dynamics simulations show the asymmetry of the rotational potential for [R-1], demonstrating the potential suitability of receptor 1 to act as a stator in a unidirectionally operating nanoratchet (see figure). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Many well-established classical biomolecular force fields, fitted on the solvation properties of single ions, do not necessarily describe all the details of ion pairing accurately, especially for complex polyatomic ions. Depending on the target application, it might not be sufficient to reproduce the thermodynamics of ion pairing, but it may also be necessary to correctly capture structural details, such as the coordination mode. In this work, we analyzed how classical force fields can be optimized to yield a realistic description of these different aspects of ion pairing. Given the prominent role of the interactions of negatively charged amino-acid side chains and divalent cations in many biomolecular systems, we chose calcium acetate as a benchmark system to devise a general optimization strategy that we applied to two popular force fields, namely, GROMOS and OPLS-AA. Using experimental association constants and first-principles molecular dynamics simulations as a reference, we found that small modifications of the van der Waals ion-ion interaction parameters allow a systematic improvement of the essential thermodynamic and structural properties of ion pairing. © 2014 American Chemical Society.

Amplitude equations are discussed as an extension of phase field models, which contain atomic resolution and allow one to describe polycrystalline structures, lattice deformations and defects. The interaction of adjacent grains, which are separated by a thin melt layer, leads to structural interactions if the grains are slightly misplaced, similar to the concept of γ-surfaces. We are able to predict these interactions essentially analytically, leading to a superposition of short-ranged interaction terms related to the individual density waves. Deviations from the analytical predictions are found only at short distances between the grains and are most pronounced in situations with different ranges of the contributions. Furthermore, we demonstrate the ability of the amplitude equation model to predict dislocation pairing transitions at high temperatures, which supports earlier findings using molecular dynamics and phase field crystal simulations. To effectively perform the numerical simulations, we present a way to implement the model on graphics cards. An enormous acceleration of the code in comparison to a single CPU code by up to two orders of magnitude is reached. © 2014 IOP Publishing Ltd.

All-atom methods treat solute and solvent at the same level of electronic structure theory and statistical mechanics. All-atom computation of acidity constants (pKa) and redox potentials is still a challenge. In this Account, we review such a method combining density functional theory based molecular dynamics (DFTMD) and free energy perturbation (FEP) methods. The key computational tool is a FEP based method for reversible insertion of a proton or electron in a periodic DFTMD model system. The free energy of insertion (work function) is computed by thermodynamic integration of vertical energy gaps obtained from total energy differences. The problem of the loss of a physical reference for ionization energies under periodic boundary conditions is solved by comparing with the proton work function computed for the same supercell. The scheme acts as a computational hydrogen electrode, and the DFTMD redox energies can be directly compared with experimental redox potentials. Consistent with the closed shell nature of acid dissociation, pKa estimates computed using the proton insertion/removal scheme are found to be significantly more accurate than the redox potential calculations. This enables us to separate the DFT error from other sources of uncertainty such as finite system size and sampling errors. Drawing an analogy with charged defects in solids, we trace the error in redox potentials back to underestimation of the energy gap of the extended states of the solvent. Accordingly the improvement in the redox potential as calculated by hybrid functionals is explained as a consequence of the opening up of the bandgap by the Hartree-Fock exchange component in hybrids. Test calculations for a number of small inorganic and organic molecules show that the hybrid functional implementation of our method can reproduce acidity constants with an uncertainty of 1-2 pKa units (0.1 eV). The error for redox potentials is in the order of 0.2 V. (Figure Presented). © 2014 American Chemical Society.

Four commonly used embedded atom method potentials for bcc-Fe by Ackland et al. (1997), Mendelev et al. (2003), Chiesa et al. (2009) and Malerba et al. (2010) are critically evaluated with respect to their description of the edge dislocation core structure and its dynamic behavior. Our results allow us to quantify the transferability of the various empirical potentials in the study of the 〈1 1 〉{1 1 0} edge dislocation core structure and kinetics. Specifically, we show that the equilibrium dislocation core structure is a direct consequence of the shape of the extended gamma surface. We further find that there is a strong correlation between the structure of the edge dislocation core and its glide stress. An in depth analysis of the dislocation migration results reveals that the dominant migration mechanism is via progressing straight line segments of the dislocation. This is further confirmed by the excellent qualitative agreement of nudged elastic band calculations of the Peierls barrier with the dynamically determined critical shear stresses. © 2014 Elsevier B.V. All rights reserved.

Values of the melting temperature at normal pressure $T_m$, of the slope of the melting line, and of the activation energies for the diffusion coefficient and viscosity are corrected. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

We use a nanoindenter with a Berkovich tip to study local mechanical properties of two polycrystalline intermetallics with a B2 crystal structure, NiAl and NiTi. We use orientation imaging scanning electron microscopy to select a relevant number of grains with appropriate sizes and surface normals parallel to 〈0 0 1〉, 〈1 0 1〉 and 〈1 1 1〉. As a striking new result, we find a strong crystallographic orientation dependence for NiTi. This anisotropy is less pronounced in the case of NiAl. For NiTi, the indentation force required to impose a specific indentation depth is highest for indentation experiments performed in the 〈0 0 1〉 direction and lowest along the 〈1 1 1〉 direction. We consider transmission electron microscopy results from cross-sections below the indents and use molecular dynamics simulations and resolved shear stress calculations to discuss how this difference can be accounted for in terms of elementary deformation and transformation processes, related to dislocation plasticity (NiAl and NiTi), and in terms of the stress-induced formation and growth of martensite (NiTi). Our results show that the crystallographic anisotropy during nanoindentation of NiTi is governed by the orientation dependence of the martensitic transformation; dislocation plasticity appears to be less important. © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The vibrational sum frequency generation (VSFG) spectrum of the water liquid-vapor (LV) interface is calculated using density functional theory-based molecular dynamics simulations. The real and imaginary parts of the spectrum are in good agreement with the experimental data, and we provide an assignment of the SFG bands according to the dipole orientation of the interfacial water molecules. We use an instantaneous definition of the surface, which is more adapted to the study of interfacial phenomena than the Gibbs dividing surface. By calculating the vibrational (infrared, Raman) properties for interfaces of varying thickness, we show that the bulk spectra signatures appear after a thin layer of 2-3 Å only. We therefore use this value as a criterion for calculating the VSFG spectrum. © 2012 American Chemical Society.

We use molecular dynamics simulations in order to understand the microscopic origin of the asymmetric growth mechanism in gold nanorods. We provide the first atomistic model of different surfaces on gold nanoparticles in a growing electrolyte solution, and we describe the interaction of the metal with the surfactants, namely, cetyltrimethylammonium bromide (CTAB) and the ions. An innovative aspect is the inclusion of the role of the surfactants, which are explicitly modeled. We find that on all the investigated surfaces, namely, (111), (110), and (100), CTAB forms a layer of distorted cylindrical micelles where channels among micelles provide direct ion access to the surface. In particular, we show how AuCl2- ions, which are found in the growth solution, can freely diffuse from the bulk solution to the gold surface. We also find that the (111) surface exhibits a higher CTAB packing density and a higher electrostatic potential. Both elements would favor the growth of gold nanoparticles along the (111) direction. These findings are in agreement with the growth mechanisms proposed by the experimental groups of Murphy and Mulvaney. © 2013 American Chemical Society.

The development of reliable interatomic potentials for large-scale molecular dynamics (MD) simulations of chemical processes at surfaces and interfaces is a formidable challenge because a wide range of atomic environments and very different types of bonding can be present. In recent years interatomic potentials based on artificial neural networks (NNs) have emerged offering an unbiased approach to the construction of potential energy surfaces (PESs) for systems that are difficult to describe by conventional potentials. Here, we review the basic properties of NN potentials and describe their construction for materials like metals and oxides. The accuracy and efficiency are demonstrated using copper and zinc oxide as benchmark systems. First results for a potential of the combined ternary CuZnO system aiming at the description of oxide-supported copper clusters are reported. Model of a copper cluster at the ZnO($10\overline {1} 0$) surface. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Water clusters have attracted a lot of attention as prototype systems to study hydrogen bonded molecular aggregates but also to gain deeper insights into the properties of liquid water, the solvent of life. All these studies depend on an accurate description of the atomic interactions and countless potentials have been proposed in the literature in the past decades to represent the potential-energy surface (PES) of water. Many of these potentials employ drastic approximations like rigid water monomers and fixed point charges, while on the other hand also several attempts have been made to derive very accurate PESs by fitting data obtained in high-level electronic structure calculations. In recent years artificial neural networks (NNs) have been established as a powerful tool to construct high-dimensional PESs of a variety of systems, but to date no full-dimensional NN PES for water has been reported. Here, we present NN potentials for water clusters containing two to six water molecules trained to density functional theory (DFT) data employing two different exchange-correlation functionals, PBE and RPBE. In contrast to other potentials fitted to first principles data, these NN potentials are not based on a truncated many-body expansion of the energy but consider the interactions between all water molecules explicitly. For both functionals an excellent agreement with the underlying DFT calculations has been found with binding energy errors of only about 1%.© by Oldenbourg Wissenschaftsverlag, München.

The nature of nanocrystalline materials determines that their deformation at the grain level relies on the orientation of individual grains. In this work, we investigate the anisotropic response of nanotwinned Cu to frictional contacts during nanoscratching by means of molecular dynamics simulations. Nanotwinned Cu samples containing embedded twin boundaries parallel, inclined and perpendicular to scratching surfaces are adopted to address the effects of crystallographic orientation and inclination angle of aligned twin boundaries cutting the scratching surface. The transition in deformation mechanisms, the evolution of friction coefficients and the friction-induced microstructural changes are analyzed in detail and are related to the loading conditions and the twinned microstructures of the materials. Furthermore, the effect of twin spacing on the frictional behavior of Cu samples is studied. Our simulation results show that the crystallographic orientation strongly influences the frictional response in different ways for samples with different twin spacing, because the dominant deformation mode varies upon scratching regions of different orientations. A critical inclination angle of 26.6° gives the lowest yield strength and the highest friction coefficient, at which the plasticity is dominated by twin boundary migration and detwinning. It is demonstrated that the anisotropic frictional response of nanotwinned Cu originates from the heterogeneous localized deformation, which is strongly influenced by crystallographic orientation, twin boundary orientation and loading condition. © 2013 IOP Publishing Ltd.

Via event-driven molecular dynamics simulations and experiments, we study the packing-fraction and shear-rate dependence of single-particle fluctuations and dynamic correlations in hard-sphere glasses under shear. At packing fractions above the glass transition, correlations increase as shear rate decreases: the exponential tail in the distribution of single-particle jumps broadens and dynamic four-point correlations increase. Interestingly, however, upon decreasing the packing fraction, a broadening of the exponential tail is also observed, while dynamic heterogeneity is shown to decrease. An explanation for this behavior is proposed in terms of a competition between shear and thermal fluctuations. Building upon our previous studies, we further address the issue of anisotropy of the dynamic correlations. © 2013 American Physical Society.

Phase change materials are of great interest as active layers in rewritable optical disks and novel electronic nonvolatile memories. These applications rest on a fast and reversible transformation between the amorphous and crystalline phases upon heating, taking place on the nanosecond time scale. In this work, we investigate the microscopic origin of the fast crystallization process by means of large-scale molecular dynamics simulations of the phase change compound GeTe. To this end, we use an interatomic potential generated from a Neural Network fitting of a large database of ab initio energies. We demonstrate that in the temperature range of the programming protocols of the electronic memories (500-700 K), nucleation of the crystal in the supercooled liquid is not rate-limiting. In this temperature range, the growth of supercritical nuclei is very fast because of a large atomic mobility, which is, in turn, the consequence of the high fragility of the supercooled liquid and the associated breakdown of the Stokes-Einstein relation between viscosity and diffusivity. © 2013 American Chemical Society.

The equilibrium structure including the network of hydrogen bonds of an α-chitin crystal is determined combining density-functional theory (DFT), self-consistent DFT-based tight-binding (SCC-DFTB), and empirical forcefield molecular dynamics (MD) simulations. Based on the equilibrium geometry several possible crystal conformations (local energy minima) have been identified and related to hydrogen bond patterns. Our results provide new insight and allow to resolve the contradicting α-chitin structural models proposed by various experiments. © 2012 Wiley Periodicals, Inc. Copyright © 2012 Wiley Periodicals, Inc.

It has been reported recently that the equipartition theorem is violated in molecular dynamics simulations with periodic boundary condition. This effect is associated with the conservation of the total momentum. Here, we propose a fluctuating center of mass molecular dynamics approach to solve this problem. Using the analogy to a system exchanging momentum with its surroundings, we work out - and validate via simulations - an expression for the rate at which fluctuations shall be added to the system. It is shown that the proposed method maintains equipartition both at equilibrium and beyond equilibrium in the linear response regime. © 2013 American Physical Society.

The fundamental importance of water for many chemical processes has motivated the development of countless efficient but approximate water potentials for large-scale molecular dynamics simulations, from simple empirical force fields to very sophisticated flexible water models. Accurate and generally applicable water potentials should fulfill a number of requirements. They should have a quality close to quantum chemical methods, they should explicitly depend on all degrees of freedom including all relevant many-body interactions, and they should be able to describe molecular dissociation and recombination. In this work, we present a high-dimensional neural network (NN) potential for water clusters based on density-functional theory (DFT) calculations, which is constructed using clusters containing up to 10 monomers and is in principle able to meet all these requirements. We investigate the reliability of specific parametrizations employing two frequently used generalized gradient approximation (GGA) exchange-correlation functionals, PBE and RPBE, as reference methods. We find that the binding energy errors of the NN potentials with respect to DFT are significantly lower than the typical uncertainties of DFT calculations arising from the choice of the exchange-correlation functional. Further, we examine the role of van der Waals interactions, which are not properly described by GGA functionals. Specifically, we incorporate the D3 scheme suggested by Grimme (J. Chem. Phys. 2010, 132, 154104) in our potentials and demonstrate that it can be applied to GGA-based NN potentials in the same way as to DFT calculations without modification. Our results show that the description of small water clusters provided by the RPBE functional is significantly improved if van der Waals interactions are included, while in case of the PBE functional, which is well-known to yield stronger binding than RPBE, van der Waals corrections lead to overestimated binding energies. © 2013 American Chemical Society.

As chromium is a decisive ingredient for stainless steels, a reliable understanding of its thermodynamic properties is indispensable. Parameter-free first-principles methods have nowadays evolved to a state allowing such thermodynamic predictions. For materials such as Cr, however, the inclusion of magnetic entropy and higher order contributions such as anharmonic entropy is still a formidable task. Employing state-of-the-art ab initio molecular dynamics simulations and statistical concepts, we compute a set of thermodynamic properties based on quasiharmonic, anharmonic, electronic and magnetic free energy contributions from first principles. The magnetic contribution is modeled by an effective nearest-neighbor Heisenberg model, which itself is solved numerically exactly by means of a quantum Monte Carlo method. We investigate two different scenarios: a weak magnetic coupling scenario for Cr, as usually presumed in empirical thermodynamic models, turns out to be in clear disagreement with experimental observations. We show that instead a mixed Hamiltonian including weak and strong magnetic coupling provides a consistent picture with good agreement to experimental thermodynamic data. © 2013 IOP Publishing Ltd.

This paper reviews our efforts to simulate methanol synthesis from CO and H2 on defective ZnO surfaces using advanced molecular dynamics techniques. This apparently simple chemical reaction occurring on a seemingly well-defined surface appears to be astonishingly complex. First of all, the preferred oxidation state of F centers at the polar oxygen terminated surface is found to be dictated by the chemical composition and the thermodynamic properties of the gas phase in contact with ${\rm ZnO}(000\overline {1} )$. Secondly, reaction intermediates and pathways along the catalytic cycle taking place at or close to these defects are found to depend in a sensitive way on their oxidation state. Thirdly, it is seen that the gas phase close to the catalytic surface might be transiently involved in some of the reaction steps in a non-trivial manner. Last but not least, the scenario is found to be greatly enriched upon involving copper clusters on polar ZnO surfaces in view of utmost strong metal-support interactions (SMSIs), which are directly related to the polar nature of ${\rm ZnO}(000\overline {1} )$. Taken together, an unexpectedly rich picture is unveiled by the molecular dynamics approach to computational heterogeneous catalysis when applied to methanol synthesis on bare ZnO.

An accurate determination of the potential energy is the crucial step in computer simulations of chemical processes, but using electronic structure methods on-the-fly in molecular dynamics (MD) is computationally too demanding for many systems. Constructing more efficient interatomic potentials becomes intricate with increasing dimensionality of the potential-energy surface (PES), and for numerous systems the accuracy that can be achieved is still not satisfying and far from the reliability of first-principles calculations. Feed-forward neural networks (NNs) have a very flexible functional form, and in recent years they have been shown to be an accurate tool to construct efficient PESs. High-dimensional NN potentials based on environment-dependent atomic energy contributions have been presented for a number of materials. Still, these potentials may be improved by a more detailed structural description, e.g., in form of atom pairs, which directly reflect the atomic interactions and take the chemical environment into account. We present an implementation of an NN method based on atom pairs, and its accuracy and performance are compared to the atom-based NN approach using two very different systems, the methanol molecule and metallic copper. We find that both types of NN potentials provide an excellent description of both PESs, with the pair-based method yielding a slightly higher accuracy making it a competitive alternative for addressing complex systems in MD simulations. © 2012 American Institute of Physics.

Crystal plasticity caused by the nucleation and interaction of dislocations is an important aspect in crystal deformation. Recent nanoindentation experiments in single crystals of copper or aluminum revealed large deviations in the lattice rotation and an inhomogeneous distribution of the dislocation density in the plastic zone under the indenter tip. Molecular dynamics simulations offer the possibility to study the origin of these phenomena on an atomistic scale, but require sophisticated analysis routines in order to deal with the massive amount of generated data. Here a new efficient approach to analyze atomistic data on the fly during the simulation is introduced. This approach allows us to identify the dislocation network including Burgers vectors on the timescale of picoseconds and below. This data does not only reveal the evolution of dislocation structures, but it offers the possibility to quantify local dislocation density tensors calculated on an atomic level. The numerical results are compared with experimental data from the literature. The presented approach provides useful insight into the active deformation mechanisms during plastic deformation that will help us to bridge simulations on atomic scales and continuum descriptions. © 2012 Elsevier Ltd. All rights reserved.

The electronic states of aqueous species can mix with the extended states of the solvent if they are close in energy to the band edges of water. Using density functional theory-based molecular dynamics simulation, we show that this is the case for OH- and Cl-. The effect is, however, badly exaggerated by the generalized gradient approximation leading to systematic underestimation of redox potentials and spurious nonlinearity in the solvent reorganization. Drawing a parallel to charged defects in wide gap solid oxides, we conclude that misalignment of the valence band of water is the main source of error turning the redox levels of OH- and Cl- in resonant impurity states. On the other hand, the accuracy of energies of levels corresponding to strongly negative redox potentials is acceptable. We therefore predict that mixing of the vertical attachment level of CO2 and the unoccupied states of water is a real effect. © 2012 American Chemical Society.

Results of molecular dynamics simulations on the response of glassy materials to an externally imposed steady shear are presented. The work highlights on one hand how the competition of the time scale imposed by the flow and the inherent structural relaxation time determines the linear or non-linear nature of the rheological response. On the other hand, the issue of flow heterogeneity in a shear melted glass is also studied. © 2012 Copyright The Indian Ceramic Society.

Many engineering challenges occur on multiple interacting length scales, e.g. during fracture atoms separate on the atomic scale while plasticity develops on the micrometer scale. To investigate the details of these events, a concurrent multiscale model is required which studies the problem at appropriate length- and time-scales: the atomistic scale and the dislocation dynamics scale. The AtoDis multiscale model is introduced, which combines atomistics and dislocation dynamicsinto a fully dynamic model that is able to simulate deformation mechanisms at finite temperature. The model uses point forces to ensure mechanical equilibrium and kinematic continuity at the interface. By resolving each interface atom analytically, and not numerically, the framework uses a coarse FEM mesh and intrinsically filters out atomistic vibrations. This multiscale model allows bi-directional dislocation transition at the interface of both models with no remnant atomic disorder. Thereby, the model is able to simulate a larger plastic zone than conventional molecular dynamics while reducing the need for constitutive dislocation dynamics equations. This contribution studies dislocation nucleation at finite temperature and investigates the absorption of dislocations into the crack wake. © 2012 IOP Publishing Ltd.

There is growing evidence that the flow of driven amorphous solids is not homogeneous, even if the macroscopic stress is constant across the system. Via event-driven molecular dynamics simulations of a hard sphere glass, we provide the first direct evidence for a correlation between the fluctuations of the local volume fraction and the fluctuations of the local shear rate. Higher shear rates do preferentially occur at regions of lower density and vice versa. The temporal behavior of fluctuations is governed by a characteristic time scale, which, when measured in units of strain, is independent of shear rate in the investigated range. Interestingly, the correlation volume is also roughly constant for the same range of shear rates. A possible connection between these two observations is discussed. © 2012 American Physical Society.

The conformation transition of poly(N-isopropylacrylamide) hydrogel as a function of the methanol mole fraction in water/methanol mixtures is studied both experimentally and by atomistic molecular dynamics simulation with explicit solvents. The composition range in which the conformation transition of the hydrogel occurs is determined experimentally at 268.15, 298.15, and 313.15 K. In these experiments, cononsolvency, i.e., collapse at intermediate methanol concentrations while the hydrogel is swollen in both pure solvents, is observed at 268.15 and 298.15 K. The composition range in which cononsolvency is present does not significantly depend on the amount of cross-linker. The conformation transition of the hydrogel is caused by the conformation transition of the polymer chains of its backbone. Therefore, conformation changes of single backbone polymer chains are studied by massively parallel molecular dynamics simulations. The hydrogel backbone polymer is described with the force field OPLS-AA, water with the SPC/E model, and methanol with the model of the GROMOS-96 force field. During simulation, the mean radius of gyration of the polymer chains is monitored. The conformation of the polymer chains is studied at 268, 298, and 330 K as a function of the methanol mole fraction. Cononsolvency is observed at 268 and 298 K, which is in agreement with the present experiments. The structure of the solvent around the hydrogel backbone polymer is analyzed using H-bond statistics and visualization. It is found that cononsolvency is caused by the fact that the methanol molecules strongly attach to the hydrogels backbone polymer, mainly with their hydroxyl group. This leads to the effect that the hydrophobic methyl groups of methanol are oriented toward the bulk solvent. The hydrogel+solvent shell hence appears hydrophobic and collapses in water-rich solvents. As more methanol is present in the solvent, the effect disappears again. © 2012 American Chemical Society.

Mechanisms leading to initiation of crazing type failure in a glassy polymer are not clearly understood. This is mainly due to the difficulty in characterizing the stress state and polymer configuration sufficiently locally at the craze initiation site. Using molecular dynamics simulations, we have now been able to access this information and have shown that the local heterogeneous deformation leads to craze initiation in glassy polymers. We found that zones of high plastic activity are constrained by their neighborhood and become unstable, initiating crazing from these sites. Furthermore, based on the constant flow stresses observed in the unstable zones, we conclude that microcavitation is the essential local deformation mode to trigger crazing in glassy polymers. Our results demonstrate the basic difference in the local deformation mode as well as the conditions that lead to either shear-yielding or crazing type failures in glassy polymers. We anticipate our paper to help in devising a new criterion for craze initiation that not only considers the stress state, but also considers local deformation heterogeneities that form the necessary condition for crazing in glassy polymers. © 2012 American Physical Society.

The organization of water at the interface with silica and alumina oxides is analysed using density functional theory-based molecular dynamics simulation (DFT-MD). The interfacial hydrogen bonding is investigated in detail and related to the chemistry of the oxide surfaces by computing the surface charge density and acidity. We find that water molecules hydrogen-bonded to the surface have different orientations depending on the strength of the hydrogen bonds and use this observation to explain the features in the surface vibrational spectra measured by sum frequency generation spectroscopy. In particular, ice-like and liquid-like features in these spectra are interpreted as the result of hydrogen bonds of different strengths between surface silanols/aluminols and water. © 2012 IOP Publishing Ltd.

In this paper it is demonstrated how nanoindentation can be used to assess the subsurface damage induced by nanomachining. To accomplish this, a characteristic difference in the nanoindentation response between plastically deformed and undeformed material is exploited. Classical molecular dynamics simulations are performed to investigate the elementary mechanisms of the irreversible plastic processes that occur during nanomachining of a copper single crystal. To mimic the experimental characterization of subsurface damage, we perform nanoindentation simulations into the machined surface. The results show that the critical contact pressure required for dislocation nucleation, i.e. the pop-in load, decreases continuously with increasing machining depth, while the indentation hardness seems widely unaffected by prior nanomachining. © 2012 Elsevier B.V. All rights reserved.

Understanding the unique properties of water still represents a significant challenge for theory and experiment. Computer simulations by molecular dynamics require a reliable description of the atomic interactions, and in recent decades countless water potentials have been reported in the literature. Still, most of these potentials contain significant approximations, for instance a frozen internal structure of the individual water monomers. Artificial neural networks (NNs) offer a promising way for the construction of very accurate potential-energy surfaces taking all degrees of freedom explicitly into account. These potentials are based on electronic structure calculations for representative configurations, which are then interpolated to a continuous energy surface that can be evaluated many orders of magnitude faster. We present a full-dimensional NN potential for the water dimer as a first step towards the construction of a NN potential for liquid water. This many-body potential is based on environment-dependent atomic energy contributions, and long-range electrostatic interactions are incorporated employing environment-dependent atomic charges. We show that the potential and derived properties like vibrational frequencies are in excellent agreement with the underlying reference density-functional theory calculations. © 2012 American Institute of Physics.

With this work we present a newly developed potential for the Fe-Al system, which is based on the analytical embedded atom method (EAM) with long range atomic interactions. The potential yields for the two most relevant phases B2-FeAl and D0 3-Fe 3Al lattice constants, elastic constants, as well as bulk and point defect formation enthalpies, which are in good agreement with experimental and other theoretical data. In addition, the phonon dispersions for B2-FeAl and D0 3-Fe 3Al show a good agreement with available experiments. The calculated lattice constants and formation enthalpy for disordered Fe-Al alloys are in good agreement with experimental data or other theoretical calculations. This indicates that the present EAM potentials of Fe-Al system is suitable for atomistic simulations of structural and kinetic properties for the Fe-Al system. © 2012 Elsevier B.V.

When nanoindenting dislocation-free regions of single crystals a so-called pop-in phenomenon is commonly observed. Molecular dynamics (MD) studies have revealed homogeneous nucleation of dislocations in a perfect crystal as a mechanism causing such pop-in behavior. In this work we transfer this knowledge gained on the atomic scale into a dislocation nucleation model that is applied within a dislocation density based crystal plasticity description. Furthermore, we develop a non-local formulation of a crystal plasticity model that is devised to yield a valid description of plasticity also in situations where the dislocation density is small or even vanishing and where conventional plasticity models fail. This is accomplished by studying the evolution of statistically stored and geometrically necessary dislocation densities separately. We apply this non-local crystal plasticity model to investigate the evolution of dislocation densities in the early stages of nanoindentation. The results of our continuum model show good agreement with MD simulations for cases where nanoindentation into an initially dislocation-free crystal is studied, i.e. where a pop-in occurs when the critical stress underneath the indenter reaches the critical value for homogeneous dislocation nucleation. After thus validating our model we study the influence of pre-existing homogeneous and local dislocation densities. Both cases show a good qualitative agreement with recent experimental findings and it is concluded that pre-existing local dislocations densities reduce the load at which a pop-in occurs and - more importantly - change the mechanism from homogeneous dislocation nucleation to rapid dislocation multiplication. In general, our results show that continuum plasticity formulations can be extended such that applications to nanoscale volumes become possible. © 2012 Elsevier Ltd. All rights reserved.

The thermochemical constants for the oxidation of tyrosine and tryptophan through proton coupled electron transfer in aqueous solution have been computed applying a recently developed density functional theory (DFT) based molecular dynamics method for reversible elimination of protons and electrons. This method enables us to estimate the solvation free energy of a proton (H+) in a periodic model system from the free energy for the deprotonation of an aqueous hydronium ion (H3O+). Using the computed solvation free energy of H+ as reference, the deprotonation and oxidation free energies of an aqueous species can be converted to pKa and normal hydrogen electrode (NHE) potentials. This conversion requires certain thermochemical corrections which were first presented in a similar study of the oxidation of hydrobenzoquinone [J. Cheng, M. Sulpizi, and M. Sprik, J. Chem. Phys. 131, 154504 (2009)]10.1063/1.3250438. Taking a different view of the thermodynamic status of the hydronium ion, these thermochemical corrections are revised in the present work. The key difference with the previous scheme is that the hydronium is now treated as an intermediate in the transfer of the proton from solution to the gas-phase. The accuracy of the method is assessed by a detailed comparison of the computed pKa, NHE potentials and dehydrogenation free energies to experiment. As a further application of the technique, we have analyzed the role of the solvent in the oxidation of tyrosine by the tryptophan radical. The free energy change computed for this hydrogen atom transfer reaction is very similar to the gas-phase value, in agreement with experiment. The molecular dynamics results however, show that the minimal solvent effect on the reaction free energy is accompanied by a significant reorganization of the solvent. © 2011 American Institute of Physics.

In order to simplify the development and implementation process of quantum mechanical algorithms, we developed a set of object-oriented C++ libraries which can exploit modern computer architectures. The libraries are characterized as follows: (i) State-of-the-art computer science techniques have been applied or developed in this work to provide language elements to express algebraic expressions efficiently on modern computer platforms. (ii) Quantum mechanical algorithms are crucial in the field of materials research. The new libraries support the Dirac notation to implement such algorithms in the native language of physicists. (iii) The libraries are completed by elements to express equations of motions efficiently which is required for implementing structural algorithms such as molecular dynamics. Based on these libraries we introduce the DFT program package S/PHI/nX. © 2010 Elsevier B.V. All rights reserved.

Absolute pKa values of the amino acid side chains of arginine, aspartate, cysteine, histidine, and tyrosine; the C- and N-terminal group of tyrosine; and the tryptophan radical cation are calculated using a revised density functional based molecular dynamics simulation technique introduced previously [Cheng, J.; Sulpizi, M.; Sprik, M.J. Chem. Phys. 2009, 131, 154504 ]. In the revised scheme, acid deprotonation is considered as a dissociation rather than a proton transfer reaction, and a correction term for treating the proton as a hydronium ion is suggested. The acidity constants of the amino acids are obtained from the vertical energy gaps for removal or insertion of the acidic proton and the computed solvation free energy of the proton. The unsigned mean error relative to experimental results is 2.1 pKa units with a maximum error of 4.0 pKa units. The estimated mean statistical uncertainty due to the finite length of the trajectories is ±1.1 pK a units. The solvation structures of the protonated and deprotonated amino acids are analyzed in terms of radial distribution functions, which can serve as reference data for future force field developments. © 2011 American Chemical Society.

Shape memory alloys (SMA) exhibit a number of features which are not easily explained by equilibrium thermodynamics, including hysteresis in the phase transformation and reverse shape memory in the high symmetry phase. Processing can change these features: repeated cycling can train the reverse shape memory effect, while changing the amount of hysteresis and other functional properties. These effects are likely to be due to formations of localised defects and these can be studied by atomistic methods. Here we present a molecular dynamics simulation study of such behaviour employing a two-dimensional, binary LennardJones model. Our atomistic model exhibits a symmetry breaking, displacive phase transition from a high temperature, entropically stabilised, austenite-like phase to a low temperature martensite-like phase. The simulations show transformations in this model material proceed by non-diffusive nucleation and growth processes and produce distinct microstructures. We observe the generation of persistent lattice defects during forward-and-reverse transformations which serve as nucleation centres in subsequent transformation processes. These defects interfere the temporal and spatial progression of transformations and thereby affect subsequent product morphologies. During cyclic transformations we observe accumulations of lattice defects so as to establish new microstructural elements which represent a memory of the previous morphologies. These new elements are self-organised and they provide a basis of the reversible shape memory effect in the model material. © 2011 Elsevier Ltd.

Recently, we proposed a hierarchical model for the elastic properties of mineralized lobster cuticle using (i) ab initio calculations for the chitin properties and (ii) hierarchical homogenization performed in a bottom-up order through all length scales. It has been found that the cuticle possesses nearly extremal, excellent mechanical properties in terms of stiffness that strongly depend on the overall mineral content and the specific microstructure of the mineral-protein matrix. In this study, we investigated how the overall cuticle properties changed when there are significant variations in the properties of the constituents (chitin, amorphous calcium carbonate (ACC), proteins), and the volume fractions of key structural elements such as chitin-protein fibers. It was found that the cuticle performance is very robust with respect to variations in the elastic properties of chitin and fiber proteins at a lower hierarchy level. At higher structural levels, variations of design parameters such as the volume fraction of the chitin-protein fibers have a significant influence on the cuticle performance. Furthermore, we observed that among the possible variations in the cuticle ingredients and volume fractions, the experimental data reflect an optimal use of the structural variations regarding the best possible performance for a given composition due to the smart hierarchical organization of the cuticle design. © 2010 Elsevier Ltd.

To enable plastic deformation during nanoindentation of an initially defect-free crystal, it is necessary first to produce dislocations. While it is now widely accepted that the nucleation of the first dislocations occurs at the start of the pop-in event frequently observed in experiments, it is unclear how these initial dislocations multiply during the early stages of plastic deformation and produce pop-in displacements that are typically much larger than the magnitude of the Burgers vector. This uncertainty about the complex interplay between dislocation multiplication and strain hardening during nanoindentation makes a direct correlation between force-displacement curves and macroscopic material properties difficult. In this paper, we study the early phase of plastic deformation during nanoindentation with the help of large-scale molecular dynamics simulations. A skeletonization method to simplify defect structures in atomistic simulations enables the direct observation and quantitative analysis of dislocation nucleation and multiplication processes occurring in the bulk as well as at the surface. © 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

In this study, the authors first review the previously developed, thermodynamics-based theory for size dependency of the cohesion energy of free-standing spherically shaped Al nanoparticles. Then, this model is extrapolated to the cubic and truncated octahedron Al nanoparticle shapes. A series of computations for Al nanoparticles with these two new shapes are presented for particles in the range of 1-100 nm. The thermodynamics computational results reveal that there is a second critical size around 1.62 and 1 nm for cubes and truncated octahedrons, respectively. Below this critical size, particles behave as if they consisted only of surface-energy-state atoms. A molecular dynamics simulation is used to verify this second critical size for Al nanoparticles in the range of 1-5 nm. MD simulation for cube and truncated octahedron shapes shows the second critical point to be around 1.63 and 1.14 nm, respectively. According to the modeling and simulation results, this second critical size seems to be a material property characteristic rather than a shape-dependent feature.

We have employed density functional theory to determine the temperature dependence of the intrinsic stability of an infinite poly-L-alanine helix. The most relevant helix types, i.e., the - and the 310 - helix, and several unfolded conformations, which serve as reference for the stability analysis, have been included. For the calculation of the free energies for the various chain conformations we have explicitly included both, harmonic and anharmonic contributions. The latter have been calculated by means of a thermodynamic integration approach employing stochastic Langevin molecular dynamics, which is shown to provide a dramatic increase in the computational efficiency as compared to commonly employed deterministic molecular dynamics schemes. Employing this approach we demonstrate that the anharmonic part of the free energy amounts to the order of 0.1-0.4 kcal/mol per peptide unit for all analysed conformations. Although small, the anharmonic contribution stabilizes the helical conformations with respect to the fully extended structure. © 2011 American Institute of Physics.

Neural networks offer an unbiased and numerically very accurate approach to represent high-dimensional ab initio potential-energy surfaces. Once constructed, neural network potentials can provide the energies and forces many orders of magnitude faster than electronic structure calculations, and thus enable molecular dynamics simulations of large systems. However, Cartesian coordinates are not a good choice to represent the atomic positions, and a transformation to symmetry functions is required. Using simple benchmark systems, the properties of several types of symmetry functions suitable for the construction of high-dimensional neural network potential-energy surfaces are discussed in detail. The symmetry functions are general and can be applied to all types of systems such as molecules, crystalline and amorphous solids, and liquids. © 2011 American Institute of Physics.

Fatigue experiments on copper have shown that vacancy production leads to the evolution of extrusions, which are the preferred sites for fatigue crack initiation. However, experimental, analytical and numerical results for the critical edge-dislocation dipole annihilation distance vastly differ. This study performs molecular statics and molecular dynamics simulations at elevated temperature to investigate the discrepancies in annihilation distance. Vacancy forming edge dislocation dipoles are stable if their spacing exceeds 2 lattice spacings. If the dislocation dipole is perpendicular to the free surface in a thin sheet of material, jogs on edge dislocations lead to dipole annihilation. Our main conclusion is that dislocation generation, glide and stable edge dislocation dipoles are sufficient to lead to that extrusion growth, which results in fatigue crack initiation.

The concentration and temperature dependence of the self-diffusion of benzene adsorbed in the metal-organic framework MOF-5 (IRMOF-1) is studied by pulsed field gradient (PFG) NMR spectroscopy. When increasing the loading from 10 to 20 molecules per unit cell of MOF-5, the experimental diffusion data drop by a factor of about 3 while current molecular dynamic (MD) simulations predict slightly increasing diffusion coefficients for this range of loadings. The observation is rationalized using the recently predicted clustering of adsorbate molecules in microporous systems for temperatures well below the adsorbate critical temperature. Necessary improvements of molecular simulation models for predicting diffusivities under such conditions are discussed. © EDP Sciences, 2011.

In this work, the indentation size effect and pop-in behavior are studied for indentations in undeformed and locally pre-deformed CaF2 single crystals, using both nanoindentation experiments and molecular dynamics simulations. To study the influence of dislocation density on the indentation behavior, small-scale indentations are carried out inside the plastic zone of larger indentations. This experiment is mimicked in the simulations by indenting a small sphere into the center of the residual impression of a larger sphere. The undeformed material shows the well-known pop-in behavior followed by the indentation size effect. Pre-deforming the material leads to a reduction in the indentation size effect both for experiments and simulations, which is in accordance with the Nix-Gao theory. Furthermore, the pop-in load is reduced in the experiments, whereas a smooth transition from elastic to plastic deformation is found in the simulations. There, plasticity is initiated by the movement of pre-existing dislocation loops in the vicinity of the plastic zone. The simulations thus give a detailed insight into the deformation mechanism during indentation and highlight the importance of the dislocation microstructure for the indentation size effect and dislocation nucleation. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Large-scale molecular dynamics simulations have been widely used to investigate the mechanical behaviour of materials. But complex datasets, involving the positions of millions of atoms, generated during the simulations make quantitative data analysis quite a challenge. This paper presents a novel method to determine not only dislocations in the crystal, but also to quantify their Burgers vectors. This is achieved by combining geometrical methods to determine the atoms lying in the dislocations cores, like for example the common neighbour analysis or the bond angle analysis, with the slip vector analysis. The first methods are used to filter out the atoms lying in undisturbed regions of the crystal; the latter method yields the relative slip of the remaining atoms and thus indicates the Burgers vector of those atoms lying in the dislocation cores. The validity of the method is demonstrated here on a single edge dislocation in a relatively small sample. Furthermore a way will be sketched how this analysis can be used to determine densities of statistically stored and geometrically necessary dislocations, respectively. Hence, this method can be expected to provide valuable input for strain gradient plasticity models. © 2010 IOP Publishing Ltd.

Using molecular-dynamics simulation we simulate nanoindentation into the three principal surfaces-the (100), (110), and (111) surface-of Cu and Al. In the elastic regime, the simulation data agree fairly well with the linear elastic theory of indentation into an elastically anisotropic substrate. With increasing indentation depth, the effect of pressure hardening becomes visible. When the critical stress for dislocation nucleation is reached, even the elastically isotropic Al shows a strong dependence of the force-displacement curves on the surface orientation. After the load drop, when plasticity has set in, the influence of the surface orientation is lost, and the contact pressure (hardness) becomes independent of the surface orientation. © 2010 American Institute of Physics.

Particle based simulation methods are well established paths to explore system behavior on microscopic to mesoscopic time and length scales. With the development of new computer architectures it becomes more and more important to concentrate on local algorithms which do not need global data transfer or reorganisation of large arrays of data across processors. This requirement strongly addresses long-range interactions in particle systems, i.e. mainly hydrodynamic and electrostatic contributions. In this article, emphasis is given to the implementation and parallelization of the Multi-Particle Collision Dynamics method for hydrodynamic contributions and a splitting scheme based on Multigrid for electrostatic contributions. Implementations are done for massively parallel architectures and are demonstrated for the IBM Blue Gene/P architecture Jugene in Jülich. © 2010 American Institute of Physics.

The properties of semidilute polymer solutions are investigated at equilibrium and under shear flow by mesoscale simulations, which combine molecular dynamics simulations and the multiparticle collision dynamics approach. In semidilute solution, intermolecular hydrodynamic and excluded volume interactions become increasingly important due to the presence of polymer overlap. At equilibrium, the dependence of the radius of gyration, the structure factor, and the zero-shear viscosity on the polymer concentration is determined and found to be in good agreement with scaling predictions. In shear flow, the polymer alignment and deformation are calculated as a function of concentration. Shear thinning, which is related to flow alignment and finite polymer extensibility, is characterized by the shear viscosity and the normal stress coefficients. © 2010 American Chemical Society.

The newly developed parallel Input/Output-libray SIONlib is applied to the highly scalable parallel multiscale code MP2C, which couples a mesoscopic fluid method based on multi-particle collision dynamics to molecular dynamics. It is demonstrated that for fluid-benchmark systems, a significant improvement of scalability under production conditions can be achieved. It is shown that for the BlueGene/P architecture at Jülich a performance close to the bandwidth capacity of 4.7 GByte/sec can be obtained. The article discusses the ease of use of SIONlib from the point of view of application. © 2010 The authors and IOS Press. All rights reserved.

In this work, multi-phase field and molecular dynamics simulations have been used to investigate nanoscale grain growth mechanisms. Based on experimental observations, the combination of grain boundary expansion and vacancy diffusion has been considered in the multi-phase field model. The atomistic mechanism of boundary movement and the free volume redistribution during the growth process have been investigated using molecular dynamics simulations. According to the multi-phase field results, linear grain growth in nanostructured materials at low temperature can be explained by vacancy diffusion in the stress field around the grain boundaries. Molecular dynamics simulations confirm the observation of linear grain growth for nanometresized grains. The activation energy of grain boundary motion in this regime has been determined to be of the order of onetenth of the self-diffusion activation energy, which is consistent with experimental data. Based on the simulation results, the transition from linear to normal grain growth is discussed in detail and a criterion for this transition is proposed. © Carl Hanser Verlag GmbH & Co. KG.

Purpose - Shape memory alloys are a fascinating class of materials because they combine both structural and functional properties. These properties strongly depend on temperature. One consequence of this dependency yields the characteristic shape-memory effect: shape memory alloys can recover processed reference configurations after significant plastic deformations simply upon a change of temperature. For real materials, such processes incorporate characteristic hysteresis. This paper aims at an understanding of these materials from an atomistic point of view. Design/methodology/approach - 2D molecular-dynamics (MD) simulations describing a chain consisting of 32 linked Lennard-Jones crystals are presented. The crystals consist of nested lattices of two atom species. Distinct lattice structures can be identified, interpreted as austenite and (variants of) martensite. Temperature and/or load-induced phase transitions between these configurations are observed in MD simulations. Previously, the thermal equation of state of one isolated crystal was investigated and its phase stability was discussed in detail. In the multi-crystal chain considered in the present paper, individual crystals contribute collectively to the thermo-mechanical behavior of the assembly. Findings - The paper presents the results of numerical experiments with this polycrystalline chain under strain-, load- and/or temperature-control. The results show that with the assumption of simple Lennard-Jones potentials of interaction between atoms in individual crystals and linking these crystals allows to reproduce the features associated with the fascinating behavior of shape memory alloys, including pseudo-plasticity, pseudo-elasticity and the shape memory effect. Originality/value - Owing to the special setup chosen, interfaces are missing between adjacent crystals in the chain assembly. The paper shows that in this situation load-induced austenite/ martensite transitions do not exhibit hysteresis in tension/compression cycles. This observation indirectly supports mesoscopic-level work in the literature which explicitly introduces interface energy to model such hysteresis. © Emerald Group Publishing Limited.

We present a flexible nonlinear reaction coordinate analysis method for the transition path ensemble based on the likelihood maximization approach developed by Peters and Trout [J. Chem. Phys. 125, 054108 (2006)]. By parametrizing the reaction coordinate by a string of images in a collective variable space, we can optimize the likelihood that the string correctly models the committor data obtained from a path sampling simulation. The collective variable space with the maximum likelihood is considered to contain the best description of the reaction. The use of the reweighted path ensemble [J. Rogal, J. Chem. Phys. 133, 174109 (2010)] allows a complete reaction coordinate description from the initial to the final state. We illustrate the method on a z-shaped two-dimensional potential. While developed for use with path sampling, this analysis method can also be applied to regular molecular dynamics trajectories. © 2010 American Institute of Physics.

Molecular dynamics (MD) simulations were performed of the structural changes occurring through the liquid-glass transition in Cu-Zr alloys. The total scattering functions (TSF), and their associated primary diffuse scattering peak positions (Kp), heights (Kh) and full-widths at half maximum (KFWHM) were used as metrics to compare the simulations to high-energy X-ray scattering data. The residuals of difference between the model and experimental TSFs are ∼0.03 for the liquids and about 0.07 for the glasses. Over the compositional range studied, Zr1-xCux (0.1 ≤ x ≤ 0.9), Kp, Kh and KFWHM show a strong dependence on composition and temperature. The simulation and experimental data correlate well between each other. MD simulation revealed that the Cu-Zr bonds undergo the largest changes during cooling of the liquid, whereas the Cu-Cu bonds change the least. Changes in the partial-pair correlations are more readily seen in the second and third shells. The Voronoi polyhedra (VP) in glasses are dominated by only a few select types that are compositionally dependent. The relative concentrations of the dominant VPs rapidly change in their relative proportion in the deeply undercooled liquid. The experimentally determined region of best glass formability, xCu 65%, shows the largest temperature dependent changes for the deeply undercooled liquid in the MD simulation. This region also exhibits very strong temperature dependence for the diffusivity and the total energy of the system. These data point to a strong topological change in the best glass-forming alloys and a concurrent change in the VP chemistry in the deeply undercooled liquid. © 2010 Taylor & Francis.

We introduce a reweighting scheme for the path ensembles in the transition interface sampling framework. The reweighting allows for the analysis of free energy landscapes and committor projections in any collective variable space. We illustrate the reweighting scheme on a two dimensional potential with a nonlinear reaction coordinate and on a more realistic simulation of the Trp-cage folding process. We suggest that the reweighted path ensemble can be used to optimize possible nonlinear reaction coordinates. © 2010 American Institute of Physics.

In this contribution we review our recently developed method for the calculation of acidity constants from density functional theory based molecular dynamics simulations. The method is based on a half reaction scheme in which protons are formally transferred from solution to the gas phase. The corresponding deprotonation free energies are computed from the vertical energy gaps for insertion or removal of protons. Combined to full proton transfer reactions, the deprotonation energies can be used to estimate relative acidity constants and also the Brønsted pKa when the deprotonation free energy of a hydronium ion is used as a reference. We verified the method by investigating a series of organic and inorganic acids and bases spanning a wide range of pKa values (20 units). The thermochemical corrections for the biasing potentials assisting and directing the insertion are discussed in some detail. © 2010 IOP Publishing Ltd.

The density functional theory based molecular dynamics (DFTMD) method for the computation of redox free energies presented in previous publications and the more recent modification for computation of acidity constants are reviewed. The method uses a half reaction scheme based on reversible insertion/removal of electrons and protons. The proton insertion is assisted by restraining potentials acting as chaperones. The procedure for relating the calculated deprotonation free energies to Brønsted acidities (pKa) and the oxidation free energies to electrode potentials with respect to the normal hydrogen electrode is discussed in some detail. The method is validated in an application to the reduction of aqueous 1,4-benzoquinone. The conversion of hydroquinone to quinone can take place via a number of alternative pathways consisting of combinations of acid dissociations, oxidations, or dehydrogenations. The free energy changes of all elementary steps (ten in total) are computed. The accuracy of the calculations is assessed by comparing the energies of different pathways for the same reaction (Hess's law) and by comparison to experiment. This two-sided test enables us to separate the errors related with the restrictions on length and time scales accessible to DFTMD from the errors introduced by the DFT approximation. It is found that the DFT approximation is the main source of error for oxidation free energies. © 2009 American Institute of Physics.

Combining photoemission and electrochemical data from the literature we argue that the difference between the vertical and adiabatic ionization energy of the aqueous hydroxide anion is 2.9 eV. We then use density functional theory based molecular dynamics to show that the solvent response to ionization is nonlinear. Adding this to the experimental data we predict a 4.1 eV difference between the energy for vertical attachment of an electron to the aqueous hydroxyl radical and the corresponding adiabatic electron affinity. This places the state accepting the electron only 2.2 eV below vacuum or 7.7 eV above the edge of the valence band of water. © 2009 American Chemical Society.