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Structural, elastic and thermal properties of cementite (Fe$_3$C) were studied using a Modified Embedded Atom Method (MEAM) potential for iron-carbon (Fe-C) alloys. Previously developed Fe and C single element potentials were used to…

Large scale atomistic simulations with suitable interatomic potentials are widely employed by scientists or engineers of different areas. Quick generation of high-quality interatomic potentials is of urgent need under present circumstances,…

Materials Science · Physics 2016-11-23 Kun Wang , Wenjun Zhu , Shifang Xiao , Jun Chen , Wangyu Hu

In this work, molecular mechanics simulations were performed using a modified embedded-atom method (MEAM) potential to generate the stress-strain responses of a series of n-alkane molecules from ethane (C$_2$H$_6$) to undecane…

The multi-component quantum theory of atoms in molecules (MC-QTAIM) analysis is done on methane, ethylene, acetylene and benzene as selected basic hydrocarbons. This is the first report on applying the MC-QTAIM analysis on polyatomic…

Chemical Physics · Physics 2015-02-10 Mohammad Goli , Shant Shahbazian

Simulations of chemical reaction probabilities in gas surface dynamics require the calculation of ensemble averages over many tens of thousands of reaction events to predict dynamical observables that can be compared to experiments. At the…

We present a second-nearest-neighbor Modified Embedded Atom Method (2NN--MEAM) potential for Scandium (Sc) and Aluminum-Scandium (Al--Sc) alloys that unifies cohesive, thermodynamic, and solidification behavior within a single transferable…

Materials Science · Physics 2025-12-11 Avik Mahata

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…

In this work, we present a machine-learned interatomic potential for the ${\alpha}$-Fe-H system based on the tabulated Gaussian Approximation Potential (tabGAP) formalism. Trained on a Density Functional Theory (DFT) dataset of atomic…

Materials Science · Physics 2025-11-27 Eetu Makkonen , Alvaro Lopez-Cazalilla , Flyura Djurabekova

In the present work we detail how the many-body potential energy landscape of interatomic potentials for carbon can be explored by utilising the nested sampling algorithm, allowing the calculation of their pressure-temperature phase diagram…

Materials Science · Physics 2022-08-23 George Marchant , Bora Karasulu , Livia B. Partay

Large-scale simulations of plastic deformation and phase transformations in alloys require reliable classical interatomic potentials. We construct an embedded-atom method potential for niobium as the first step in alloy potential…

Materials Science · Physics 2010-04-27 Michael R. Fellinger , Hyoungki Park , John W. Wilkins

We present a general-purpose machine learning (ML) interatomic potential for carbon and hydrogen which is capable of simulating various materials and molecules composed of these elements. This ML interatomic potential is trained using the…

Chemical Physics · Physics 2024-09-13 Rina Ibragimova , Mikhail S. Kuklin , Tigany Zarrouk , Miguel A. Caro

Developing reliable interatomic potential models with quantified predictive accuracy is crucial for atomistic simulations. Commonly used potentials, such as those constructed through the embedded atom method (EAM), are derived from…

Materials Science · Physics 2022-08-05 Arun Hegde , Elan Weiss , Wolfgang Windl , Habib N. Najm , Cosmin Safta

The behavior of hydrogen in iron and iron alloys is of interest in many fields of physics and materials science. To enable large-scale molecular dynamics simulations of systems with Fe-H interactions, we develop, based on density-functional…

Materials Science · Physics 2016-04-12 Pekko Kuopanportti , Erin Hayward , Chu-Chun Fu , Antti Kuronen , Kai Nordlund

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…

Materials Science · Physics 2018-03-23 Livia B. Partay

Based on an analysis of the short range chemical environment of each atom in a system, standard machine learning based approaches to the construction of interatomic potentials aim at determining directly the central quantity which is the…

Materials Science · Physics 2015-08-05 S. Alireza Ghasemi , Albert Hofstetter , Santanu Saha , Stefan Goedecker

In this work, we consider the hydrogen atom confined inside a penetrable spherical potential. The confining potential is described by an inverted-Gaussian function of depth $\omega_0$, width $\sigma$ and centered at $r_c$. In particular,…

Atomic Physics · Physics 2022-08-30 H. Olivares-Pilón , A. M. Escobar-Ruíz , M. A. Quiroz-Juárez , N. Aquino

Through detailed comparisons between Embedded Atom Method (EAM) and first-principles calculations for Al, we find that EAM tends to fail when there are large electron density gradients present. We attribute the observed failures to the…

Mesoscale and Nanoscale Physics · Physics 2009-01-30 Gang Wu , Gang Lu , Carlos J. Garcia-Cervera , Weinan E

Accurate modeling in the warm dense matter regime is a persistent challenge with the most detailed models such as quantum molecular dynamics and path integral Monte Carlo being immensely computationally expensive. Density functional theory…

Materials Science · Physics 2024-09-04 Sameen Yunus , David A. Strubbe

We develop a method to fit high-temperature Gibbs free energy data for the development of interatomic potentials for atomic systems. The approach is based on Hamiltonian thermodynamic integration, enabling the identification of suitable…

Materials Science · Physics 2026-03-04 Liangrui Wei , Yang Sun

We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorphous elemental carbon. Based on a machine-learning representation of the density-functional theory (DFT) potential-energy surface, such…

Materials Science · Physics 2017-03-08 Volker L. Deringer , Gábor Csányi