相关论文: Interatomic Fe-H potential for irradiation and emb…
Controlling the contamination of silicon materials by iron, especially dissolved interstitial iron (Fe$_{\mathrm{i}}$), is a longstanding problem with recent developments and several open issues. Among these we have the question whether…
Scattering and ionizing cross sections and rates are calculated for ultracold collisions between metastable helium atoms using a fully quantum-mechanical close-coupled formalism. Homonuclear collisions of the bosonic ${}^{4}$He$^{*}…
Hydrogen is a promising candidate for the light element in terrestrial planetary cores. Its incorporation into iron causes significant volume expansion, leading to a substantial density deficit. Although extensive studies have been…
We propose a new statistical physics model to study equilibrium solute segregation at grain boundaries and the resulting embrittlement effect. This low-temperature expansion model is general and efficient, and its parameters can be obtained…
The Fe pressure-temperature phase diagram and its melting line have a wide range of applications, including providing constraints for iron-core planetary models. We propose an equation of state (EOS) model based on the interstitial theory…
Borosilicate glasses are traditionally challenging to model using atomic scale simulations due to the composition and thermal history dependence of the coordination state of B atoms. Here, we report a new empirical interatomic potential…
We present a formalism for coupling a density functional theory-based quantum simulation to a classical simulation for the treatment of simple metallic systems. The formalism is applicable to multiscale simulations in which the part of the…
We develop and compare four interatomic potentials for iron: a simple machine-learned embedded atom method (EAM) potential, a potential with machine-learned two- and three-body-dependent terms, a potential with machine-learned EAM and…
We introduce an interatomic potential for hexagonal boron nitride (hBN) based on the Gaussian approximation potential (GAP) machine learning methodology. The potential is based on a training set of configurations collected from density…
The discovery of ferroelectricity in HfO$_2$-based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and high-density non-volatile memories. The functional performances…
Various mechanisms have been proposed for hydrogen embrittlement, but the causation of hydrogen-induced material degradation has remained unclear. This work shows hydrogen embrittlement due to phase instability (decomposition). In-situ…
The simulation of borosilicate glasses is challenging due to the composition and temperature dependent coordination state of boron atoms. Here, we present a newly developed machine learning optimized classical potential for molecular…
Understanding electrochemical interfaces at a microscopic level is essential for elucidating important electrochemical processes in electrocatalysis, batteries and corrosion. While \textit{ab initio} simulations have provided valuable…
The effect of interstitial hydrogen on the elastic properties of $\alpha$-iron is investigated using \textit{ab initio} density functional theory. We find that while the overall strength properties are reduced by H, the effects are mainly…
Artificial neural network potentials (NNPs) have emerged as effective tools for understanding atomic interactions at the atomic scale in various phenomena. Recently, we developed highly transferable NNPs for {\alpha}-iron and…
Choice of appropriate force field is one of the main concerns of any atomistic simulation that needs to be seriously considered in order to yield reliable results. Since, investigations on mechanical behavior of materials at micro/nanoscale…
In order to study the performance of interatomic potentials and their reliability at higher pressures, the phase diagram of four different embedded-atom type potential models of iron is compared. The calculations were done by the nested…
We created a computational workflow to analyze the potential energy surface (PES) of materials using machine-learned interatomic potentials in conjunction with the minima hopping algorithm. We demonstrate this method by producing a…
Interatomic potentials are essential for molecular dynamics simulations of magnetic materials, yet incorporating magnetic features into potentials for complex antiferromagnets remains challenging. Nickel oxide (NiO), a prototypical cubic…
The basic idea of Frozen-Density Embedding Theory (FDET) is the constrained minimisation of the Hohenberg-Kohn density functional $E^{HK}[\rho]$ performed using the auxiliary functional $E_{v_{AB}}^{FDET}[\Psi_A,\rho_B]$, where $\Psi_A$ is…