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Related papers: Models for adatom diffusion on fcc(001) metal surf…

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A modification of an embedded-atom method (EAM)-type potential is proposed for a quantitative description of equilibrium and non-equilibrium properties of metal systems within the molecular-dynamics framework. The modification generalizes…

Mesoscale and Nanoscale Physics · Physics 2021-07-09 Alexey Verkhovtsev , Andrei V. Korol , Gennady Sushko , Stefan Schramm , Andrey V. Solov'yov

In simulations of metallic interfaces, a critical aspect of metallic behavior is missing from the some of the most widely used classical molecular dynamics force fields. We present a modification of the embedded atom method (EAM) which…

Materials Science · Physics 2019-04-02 Hemanta Bhattarai , Kathie E. Newman , J. Daniel Gezelter

Calculations of the diffusion of a Au adatom on the dimer reconstructed Si(100)-2x1 surface reveal an interesting mechanism that differs significantly from a direct path between optimal binding sites, which are located in between dimer…

Materials Science · Physics 2022-05-18 Alejandro Peña-Torres , Abid Ali , Michail Stamatakis , Hannes Jónsson

A comprehensive study on the applications of denoising diffusion models for wireless systems is provided. The article highlights the capabilities of diffusion models in learning complicated signal distributions, modeling wireless channels,…

Information Theory · Computer Science 2025-12-10 Mehdi Letafati , Samad Ali , Matti Latva-aho

The rate of diffusion of a Cu adatom on the Cu(100) surface is calculated using thermodynamic integration within the transition state theory. The results are found to be in excellent agreement with the essentially exact values from…

Materials Science · Physics 2009-10-31 Ghyslain Boisvert , Normand Mousseau , Laurent J. Lewis

Gold-Silver (Au-Ag) core-shell nanostructures are gaining importance in stretchable electronics where high tensile and fatigue resistance is of paramount importance. This work proposes the parameterization of a modified embedded atomic…

We present an embedding technique for metallic systems that makes it possible to model energy dissipation into substrate phonons during surface chemical reactions from first principles. The separation of chemical and elastic contributions…

Materials Science · Physics 2014-05-14 Jörg Meyer , Karsten Reuter

The diffusion of atoms and radicals on interstellar dust grains is a fundamental ingredient for predicting accurate molecular abundances in astronomical environments. Quantitative values of diffusivity and diffusion barriers usually rely…

Astrophysics of Galaxies · Physics 2021-12-22 Viktor Zaverkin , Germán Molpeceres , Johannes Kästner

Simulating long-term mass diffusion kinetics with atomic precision is important to predict chemical and mechanical properties of alloys over time scales of engineering interest in applications, including (but not limited to) alloy heat…

Materials Science · Physics 2025-06-25 Shashank Saxena , Prateek Gupta , Dennis M. Kochmann

The boundary element method (BEM) enables solving three-dimensional electromagnetic problems using a two-dimensional surface mesh, making it appealing for applications ranging from electrical interconnect analysis to the design of…

Numerical Analysis · Mathematics 2021-12-14 Shashwat Sharma , Piero Triverio

This paper presents an analytical framework for the analysis of time-varying metal-based metamaterials. Concretely, we particularize the study to time-modulated metal-air interfaces embedded between two different semi-infinite media that…

A combination of reaction-diffusion models with moving-boundary problems yields a system in which the diffusion (spreading and penetration) and reaction (transformation) evolve the system's state and geometry over time. These systems can be…

Computational Engineering, Finance, and Science · Computer Science 2020-08-26 Mojtaba Barzegari , Liesbet Geris

Evidence accumulation models (EAMs) provide a powerful framework for inferring latent cognitive processes from choice and reaction time data. While EAMs are traditionally limited to binary choices, recent developments have extended them to…

Methodology · Statistics 2026-05-12 Yufei Wu , Tamás Szűcs , Agnes Moors , Francis Tuerlinckx

Atomic and molecular scattering at semiconductor interfaces plays a central role in surface chemistry and catalysis, yet predictive simulations remain challenging due to strong nonadiabatic effects causing the breakdown of the…

Materials Science · Physics 2026-01-16 Xiaohan Dan , Zhuoran Long , Tianyin Qiu , Jan Paul Menzel , Qiang Shi , Victor S. Batista

Diffusion models, a powerful and universal generative AI technology, have achieved tremendous success in computer vision, audio, reinforcement learning, and computational biology. In these applications, diffusion models provide flexible…

Machine Learning · Computer Science 2024-04-12 Minshuo Chen , Song Mei , Jianqing Fan , Mengdi Wang

Predicting atomic-scale crack propagation in aluminum nitride (AlN) is critical for semiconductor reliability but remains prohibitively expensive via molecular dynamics (MD). We develop a diffusion-based generative machine learning model to…

Materials Science · Physics 2026-03-17 Jiali Lu , Shengfeng Yang

Experimental diffraction patterns produced by grazing scattering of fast helium atoms from a Ag(110) surface are used as a sensitive tool to test both the scattering and the potential models. To describe the elastic collision process we…

Atomic Physics · Physics 2013-03-12 C. A. Ríos Rubiano , G. A. Bocan , M. S. Gravielle , N. Bundaleski , H. Khemliche , P. Roncin

We propose an energy-stable parametric finite element method (ES-PFEM) to discretize the motion of a closed curve under surface diffusion with an anisotropic surface energy $\gamma(\theta)$ -- anisotropic surface diffusion -- in two…

Numerical Analysis · Mathematics 2021-10-26 Yifei Li , Weizhu Bao

Generative models have become significant assets in the exploration and identification of new materials, enabling the rapid proposal of candidate crystal structures that satisfy target properties. Despite the increasing adoption of diverse…

Machine Learning · Computer Science 2025-10-21 Charles Rhys Campbell , Aldo H. Romero , Kamal Choudhary

We propose a new semiparametric approach for modelling nonlinear univariate diffusions, where the observed process is a nonparametric transformation of an underlying parametric diffusion (UPD). This modelling strategy yields a general class…

Econometrics · Economics 2020-05-08 Ruijun Bu , Kaddour Hadri , Dennis Kristensen