arXiv subjects

Y. Mishin

Publications and source records attributed to Y. Mishin.

At least 19 recordsLinked to original sources

arXiv2026

Interatomic potentials for platinum

We present two new interatomic potentials for platinum (Pt) in angular-dependent potential (ADP) and modified Tersoff (MT) formats. Both potentials have been trained on a reference database of first-principles calculations without using experimental data. The properties of Pt predicted by the ADP and MT potentials agree better with DFT calculations and experimental data than the potentials available in the literature. Future applications of the MT model to mixed-bonding metal-covalent systems are discussed.

cond-mat.mtrl-sci↗

arXiv2024

The origin of strings and rings in the atomic dynamics of disordered systems

It has long been believed that the atomic dynamics in disordered structures, such as undercooled liquids and pre-melted interfaces, are characterized by collective atomic rearrangements in the form of quasi-one-dimensional chains of atomic displacements (strings) and their closed forms (rings). Here, we show by molecular dynamics (MD) simulations that strings involving more than a few atoms do not form by a single collective event. Instead, they represent trajectories of propagating local density perturbations, which we call densitons. The atoms on this trajectory are almost indistinguishable from their environments except for the moving head of the string (densiton). A densiton migrates by either single-atom jumps or a concerted rearrangement of 2-3 atoms. The simulations reveal a remarkable similarity between the strings in disordered and crystalline structures, in which the densitons localize into point defects. This work calls for a significant reinterpretation of the string concept and instead proposes a densiton model of the atomic dynamics.

cond-mat.soft↗

arXiv2024

First-principles prediction of point defect energies and concentrations in the tantalum and hafnium carbides

First-principles calculations are combined with a statistical-mechanical model to predict the equilibrium point-defect concentrations in the refractory carbides TaC and HfC as a function of temperature and chemical composition. Several different types of point defects (vacancies, interstitials, antisite atoms) and their clusters are treated in a unified manner. The defect concentrations either strictly follow or can be closely approximated by Arrhenius functions with parameters predicted by the model. The model is general and applicable to other carbides, nitrides, borides, or similar chemical compounds. Implications of this work for understanding the diffusion mechanisms in TaC and HfC are discussed.

cond-mat.mtrl-sci↗

arXiv2023

Stochastic model and kinetic Monte Carlo simulation of solute interactions with stationary and moving grain boundaries. I. Model formulation and application to one-dimensional systems

A simple stochastic model of solute drag by moving grain boundaries (GBs) is presented. Using a small number of parameters, the model describes solute interactions with GBs and captures nonlinear GB dynamics, solute saturation in the segregation atmosphere, and the breakaway from the atmosphere. The model is solved by kinetic Monte-Carlo (KMC) simulations with time-dependent transition barriers. The non-Markovian nature of the KMC process is discussed. In Part I of this work, the model is applied to planar GBs driven by an external force. The model reproduces all basic features of the solute drag effect, including the maximum of the drag force at a critical GB velocity. The force-velocity functions obtained depart from the scaling predicted by the classical models by Cahn and Lücke-Stüwe, which are based on more restrictive assumptions. The paper sets the stage for Part II, in which the GB will be treated as a 2D solid-on-solid interface.

cond-mat.mtrl-sci↗

arXiv2023

Stochastic model and kinetic Monte Carlo simulation of solute interactions with stationary and moving grain boundaries. II. Application to two-dimensional systems

In Part I of this work, we proposed a stochastic model describing solute interactions with stationary and moving grain boundaries (GBs) and applied it to planar GBs in 1D systems. The model reproduces nonlinear GB dynamics, solute saturation in the segregation atmosphere, and all basic features of the solute drag effect. Part II of this work extends the model to 2D GBs represented by solid-on-solid interfaces. The model predicts a GB roughening transition in stationary GBs and reversible dynamic roughening in moving GBs. The impacts of the GB roughening on GB migration mechanisms, GB mobility, and the solute drag are studied in detail. The threshold effect in GB dynamics is explained by the dynamic roughening transition, which is amplified in the presence of solute segregation. The simulation results are compared with the classical models by Cahn and Lücke-Stüwe and previous computer simulations.

cond-mat.mtrl-sci↗

arXiv2021

Machine-learning interatomic potentials for materials science

Large-scale atomistic computer simulations of materials rely on interatomic potentials providing computationally efficient predictions of energy and Newtonian forces. Traditional potentials have served in this capacity for over three decades. Recently, a new class of potentials has emerged, which is based on a radically different philosophy. The new potentials are constructed using machine-learning (ML) methods and a massive reference database generated by quantum-mechanical calculations. While the traditional potentials are derived from physical insights into the nature of chemical bonding, the ML potentials utilize a high-dimensional mathematical regression to interpolate between the reference energies. We review the current status of the interatomic potential field, comparing the strengths and weaknesses of the traditional and ML potentials. A third class of potentials is introduced, in which an ML model is coupled with a physics-based potential to improve the transferability to unknown atomic environments. The discussion is focused on potentials intended for materials science applications. Possible future directions in this field are outlined.

cond-mat.mtrl-sci↗

arXiv2020

Development of a general-purpose machine-learning interatomic potential for aluminum by the physically-informed neural network method

Abstract Interatomic potentials constitute the key component of large-scale atomistic simulations of materials. The recently proposed physically-informed neural network (PINN) method combines a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential applicable to both metals and nonmetals. In this paper, we present a modified version of the PINN method that accelerates the potential training process and further improves the transferability of PINN potentials to unknown atomic environments. As an application, a modified PINN potential for Al has been developed by training on a large database of electronic structure calculations. The potential reproduces the reference first-principles energies within 2.6 meV per atom and accurately predicts a wide spectrum of physical properties of Al. Such properties include, but are not limited to, lattice dynamics, thermal expansion, energies of point and extended defects, the melting temperature, the structure and dynamic properties of liquid Al, the surface tensions of the liquid surface and the solid-liquid interface, and the nucleation and growth of a grain boundary crack. Computational efficiency of PINN potentials is also discussed.

physics.comp-ph↗

arXiv2020

Atomistic study of grain-boundary segregation and grain-boundary diffusion in Al-Mg alloys

Mg grain boundary (GB) segregation and GB diffusion can impact the processing and properties of Al-Mg alloys. Yet, Mg GB diffusion in Al has not been measured experimentally or predicted by simulations. We apply atomistic computer simulations to predict the amount and the free energy of Mg GB segregation, and the impact of segregation on GB diffusion of both alloy components. At low temperatures, Mg atoms segregated to a tilt GB form clusters with highly anisotropic shapes. Mg diffuses in Al GBs slower than Al itself, and both components diffuse slowly in comparison with Al GB self-diffusion. Thus, Mg segregation significantly reduces the rate of mass transport along GBs in Al-Mg alloys. The reduced atomic mobility can be responsible for the improved stability of the microstructure at elevated temperatures.

cond-mat.mtrl-sci↗

arXiv2020

Direct atomistic modeling of solute drag by moving grain boundaries

We show that molecular dynamics (MD) simulations are capable of reproducing the drag of solute segregation atmospheres by moving grain boundaries (GBs). Although lattice diffusion is frozen out on the MD timescale, the accelerated GB diffusion provides enough atomic mobility to allow the segregated atoms to follow the moving GB. This finding opens the possibility of studying the solute drag effect with atomic precision using the MD approach. We demonstrate that a moving GB activates diffusion and alters the short-range order in the lattice regions swept during its motion. It is also shown that a moving GB drags an atmosphere of non-equilibrium vacancies, which accelerate diffusion in surrounding lattice regions.

cond-mat.mtrl-sci↗

arXiv2020

Relationship between grain boundary segregation and grain boundary diffusion in Cu-Ag alloys

While it is known that alloy components can segregate to grain boundaries (GBs), and that the atomic mobility in GBs greatly exceeds the atomic mobility in the lattice, little is known about the effect of GB segregation on GB diffusion. Atomistic computer simulations offer a means of gaining insights into the segregation-diffusion relationship by computing the GB diffusion coefficients of the alloy components as a function of their segregated amounts. In such simulations, thermodynamically equilibrium GB segregation is prepared by a semi-grand canonical Monte Carlo method, followed by calculation of the diffusion coefficients of all alloy components by molecular dynamics. As a demonstration, the proposed methodology is applied to a GB is the Cu-Ag system. The GB diffusivities obtained exhibit non-trivial composition dependencies that can be explained by site blocking, site competition, and the onset of GB disordering due to the premelting effect.

cond-mat.mtrl-sci↗

arXiv2019

Effect of Vacancy Creation and Annihilation on Grain Boundary Motion

Interaction of vacancies with grain boundaries (GBs) is involved in many processes occurring in materials, including radiation damage healing, diffusional creep, and solid-state sintering. We analyze a model describing a set of processes occurring at a GB in the presence of a non-equilibrium, non-homogeneous vacancy concentration. Such processes include vacancy diffusion toward, away from, and across the GB, vacancy generation and absorption at the GB, and GB migration. Numerical calculations within this model reveal that the coupling among the different processes gives rise to interesting phenomena, such as vacancy-driven GB motion and accelerated vacancy generation/absorption due to GB motion. The key combinations of the model parameters that control the kinetic regimes of the vacancy-GB interactions are identified via a linear stability analysis. Possible applications and extensions of the model are discussed.e's comments

cond-mat.mtrl-sci↗

arXiv2019

Solute drag and dynamic phase transformations in moving grain boundaries

A discrete model and the regular solution approximation are applied to describe the effect of grain boundary motion on grain boundary phase transformations in a binary alloy. The model predicts all thermodynamic properties of the grain boundary and the solute drag force, and permits a broad exploration of the parameter space and different dynamic regimes. The grain boundary phases continue to exist in the moving grain boundary and show a dynamic hysteresis loop, a dynamic critical line, and other features that are similar to those for equilibrium phases. Grain boundary motion strongly affects the relative stability of the phases and can even stabilize phases that are absolutely unstable under equilibrium conditions. Grain boundary phase transformations are accompanied by drastic changes in the boundary mobility. The results are analyzed in the context of non-equilibrium thermodynamics. Unresolved problems and future work are discussed.

cond-mat.mtrl-sci↗

arXiv2019

Unraveling the dislocation core structure at a van der Waals gap in bismuth telluride

Tetradymite-structured chalcogenides such as bismuth telluride Bi_{2}Te_{3} are of significant interest for thermoelectric energy conversion and as topological insulators. Dislocations play a critical role during synthesis and processing of such materials and can strongly affect their functional properties. The dislocations between quintuple layers present special interest since their core structure is controlled by the van der Waals interactions between the layers. In this work, using atomic-resolution electron microscopy, we resolve the basal dislocation core structure in Bi_{2}Te_{3}, quantifying the disregistry of the atomic planes across the core. We show that, despite the existence of a stable stacking fault in the basal plane gamma surface, the dislocation core spreading is mainly due to the weak bonding between the layers, which leads to a small energy penalty for layer sliding parallel to the van der Waals gap. Calculations within a semidiscrete variational Peierls-Nabarro model informed by first-principles calculations support our experimental findings.

cond-mat.mtrl-sci↗

arXiv2019

An atomistic view of grain boundary diffusion

This paper presents an overview of recent computer simulations of grain boundary (GB) diffusion focusing on atomistic understanding of diffusion mechanisms. At low temperatures when GB structure is ordered, diffusion is mediated by point defects inducing collective jumps of several atoms forming a chain. At high temperatures when GB structure becomes highly disordered, the diffusion process can be analyzed by statistical methods developed earlier for supercooled liquids and glasses. Previous atomistic simulations reported in the literature as well as the new simulations presented in this paper reveal a close similarity between diffusion mechanisms in GBs and in supercooled liquids. GB diffusion at high temperatures is dominated by collective displacements of atomic groups (clusters), many of which have one-dimensional geometries similar to strings. The recent progress in this field motivates future extensions of atomistic simulations to diffusion in alloy GBs, particularly in glass-forming systems.

cond-mat.mtrl-sci↗

arXiv2019

Physically-informed artificial neural networks for atomistic modeling of materials

Large-scale atomistic computer simulations of materials heavily rely on interatomic potentials predicting the potential energy and Newtonian forces on atoms. Traditional interatomic potentials are based on physical intuition but contain few adjustable parameters and are usually not accurate. The emerging machine-learning (ML) potentials achieve highly accurate interpolation between the energies in a large DFT database but, being purely mathematical constructions, suffer from poor transferability to unknown structures. We propose a new approach that can drastically improve the transferability of ML potentials by informing them of the physical nature of interatomic bonding. This is achieved by combining a rather general physics-based model (analytical bond-order potential) with a neural-network regression. The network adjusts the parameters of the physics-based model on the fly during the simulations according to the local environments of individual atoms. This approach, called the physically-informed neural network (PINN) potential, is demonstrated by developing a general-purpose PINN potential for Al. The potential provides a DFT-level accuracy of energy predictions and excellent agreement with experimental and DFT data for a wide range of physical properties. We suggest that the development of physics-based ML potentials is the most effective way forward in the field of atomistic simulations.

cond-mat.mtrl-sci↗

arXiv2017

An optimized interatomic potential for silicon and its application to thermal stability of silicene

An optimized interatomic potential has been constructed for silicon using a modified Tersoff model. The potential reproduces a wide range of properties of Si and improves over existing potentials with respect to point defect structures and energies, surface energies and reconstructions, thermal expansion, melting temperature and other properties. The proposed potential is compared with three other potentials from the literature. The potentials demonstrate reasonable agreement with first-principles binding energies of small Si clusters as well as single-layer and bilayer silicenes. The four potentials are used to evaluate the thermal stability of free-standing silicenes in the form of nano-ribbons, nano-flakes and nano-tubes. While single-layer silicene is mechanically stable at zero Kelvin, it is predicted to become unstable and collapse at room temperature. By contrast, the bilayer silicene demonstrates a larger bending rigidity and remains stable at and even above room temperature. The results suggest that bilayer silicene might exist in a free-standing form at ambient conditions.

cond-mat.mtrl-sci↗

arXiv2016

Energy spectrum of a Langevin oscillator

We derive analytical solutions for the autocorrelation and cross-correlation functions of the kinetic, potential and total energy of a Langevin oscillator. These functions are presented in both the time and frequency domains and validated by independent numerical simulations. The results are applied to address the long-standing issue of temperature fluctuations in canonical systems.

cond-mat.other↗

arXiv2016

Temperature fluctuations in canonical systems: Insights from molecular dynamics simulations

Molecular dynamics simulations of a quasi-harmonic solid are conducted to elucidate the meaning of temperature fluctuations in canonical systems and validate a well-known but frequently contested equation predicting the mean square of such fluctuations. The simulations implement two virtual and one physical (natural) thermostat and examine the kinetic, potential and total energy correlation functions in the time and frequency domains. The results clearly demonstrate the existence of quasi-equilibrium states in which the system can be characterized by a well-defined temperature that follows the mentioned fluctuation equation. The emergence of such states is due to the wide separation of timescales between thermal relaxation by phonon scattering and slow energy exchanges with the thermostat. The quasi-equilibrium states exist between these two timescales when the system behaves as virtually isolated and equilibrium.

cond-mat.stat-mech↗