Identifying interatomic potentials for the accurate modeling of interfacial segregation and structural transitions
Sign Up to like & getrecommendations! Published in 2018 at "Computational Materials Science"
DOI: 10.1016/j.commatsci.2018.02.020
Abstract: Chemical segregation and structural transitions at interfaces are important nanoscale phenomena, making them natural targets for atomistic modeling, yet interatomic potentials must be fit to secondary physical properties. To isolate the important factors that interatomic… read more here.
Keywords: segregation structural; potentials accurate; structural transitions; interatomic potentials ... See more keywords
EAPOTs: An integrated empirical interatomic potential optimization platform for single elemental solids
Sign Up to like & getrecommendations! Published in 2021 at "Computational Materials Science"
DOI: 10.1016/j.commatsci.2021.110626
Abstract: Abstract The development of high-fidelity, empirical, interatomic potentials is in high demand since it determines the reliability and quality of atomistic simulations, such as molecular dynamics/statics (MD/MS) and Monte Carlo (MC) simulations; however, it is… read more here.
Keywords: optimization; single elemental; elemental solids; platform ... See more keywords
Prediction of the diffusion characteristics of the V-Cr system by molecular dynamics based on N-body interatomic potentials
Sign Up to like & getrecommendations! Published in 2021 at "Computational Materials Science"
DOI: 10.1016/j.commatsci.2021.110648
Abstract: Abstract Molecular dynamics (MD) is a promising method for predicting the diffusion characteristics of materials. However, the reliability of MD simulation results is largely determined by the technique of their interpretation and the interatomic potentials… read more here.
Keywords: system; agreement; diffusion; molecular dynamics ... See more keywords
A systematic study on the MEAM interatomic potentials of the transition metal nitrides TMNs (TM=Ti, V, Cr, Fe) binary systems
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Alloys and Compounds"
DOI: 10.1016/j.jallcom.2019.07.114
Abstract: Abstract The second nearest-neighbor modified embedded-atom method (2NN MEAM) interatomic potentials for the transition metal nitrides TMNs (TM = Ti, V, Cr, Fe) binary systems have been developed according to a new regulation. The obtained potentials can… read more here.
Keywords: potentials transition; transition metal; meam interatomic; interatomic potentials ... See more keywords
New interatomic potentials of W, Re and W-Re alloy for radiation defects
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Nuclear Materials"
DOI: 10.1016/j.jnucmat.2018.01.059
Abstract: Abstract Tungsten (W) and W-based alloys have been considered as promising candidates for plasma-facing materials (PFMs) in future fusion reactors. The formation of rhenium (Re)-rich clusters and intermetallic phases due to high energy neutron irradiation… read more here.
Keywords: radiation defects; new interatomic; energy; potentials alloy ... See more keywords
Improving accuracy of interatomic potentials: more physics or more data? A case study of silica
Sign Up to like & getrecommendations! Published in 2019 at "Materials Today Communications"
DOI: 10.1016/j.mtcomm.2018.11.008
Abstract: Abstract In this paper we test two strategies to improving the accuracy of machine-learning potentials, namely adding more fitting parameters thus making use of large volumes of available quantum-mechanical data, and adding a charge-equilibration model… read more here.
Keywords: physics; potentials physics; improving accuracy; accuracy ... See more keywords
Atomistic modeling of the mechanical properties: the rise of machine learning interatomic potentials.
Sign Up to like & getrecommendations! Published in 2023 at "Materials horizons"
DOI: 10.1039/d3mh00125c
Abstract: Since the birth of the concept of machine learning interatomic potentials (MLIPs) in 2007, a growing interest has been developed in the replacement of empirical interatomic potentials (EIPs) with MLIPs, in order to conduct more… read more here.
Keywords: interatomic potentials; machine learning; modeling mechanical; mechanical properties ... See more keywords
Understanding the thermal properties of amorphous solids using machine-learning-based interatomic potentials
Sign Up to like & getrecommendations! Published in 2018 at "Molecular Simulation"
DOI: 10.1080/08927022.2018.1447107
Abstract: Abstract Understanding the thermal properties of disordered systems is of fundamental importance for condensed matter physics - and for practical applications as well. While quantities such as the thermal conductivity are usually well characterised experimentally,… read more here.
Keywords: machine learning; understanding thermal; amorphous solids; interatomic potentials ... See more keywords
Evaluating the applicability of classical and neural network interatomic potentials for modeling body centered cubic polymorph of magnesium
Sign Up to like & getrecommendations! Published in 2022 at "Modelling and Simulation in Materials Science and Engineering"
DOI: 10.1088/1361-651x/ac5ebc
Abstract: Magnesium (Mg) is one of the most abundant metallic elements in nature and presents attractive mechanical properties in the industry. Particularly, it has a low density and relatively high strength/weight and stiffness/weight ratios, which make… read more here.
Keywords: neural network; potentials modeling; bcc; body centered ... See more keywords
Accurate reproduction of strongly repulsive interatomic potentials
Sign Up to like & getrecommendations! Published in 2020 at "Physical Review A"
DOI: 10.1103/physreva.101.032504
Abstract: Knowledge of the repulsive behavior of potential energy curves $V(R)$ at $R\to0$ is necessary for understanding and modeling irradiation processes of practical interest. $V(R)$ is in principle straightforward to obtain from electronic structure calculations; however,… read more here.
Keywords: accurate reproduction; reproduction strongly; strongly repulsive; interatomic potentials ... See more keywords
Dual adaptive sampling and machine learning interatomic potentials for modeling materials with chemical bond hierarchy
Sign Up to like & getrecommendations! Published in 2021 at "Physical Review B"
DOI: 10.1103/physrevb.104.094310
Abstract: The development of reliable and flexible machine learning based interatomic potentials (ML-IPs) is becoming increasingly important in studying the physical properties of complex condensed matter systems. Besides the structure descriptor model for total energy decomposition,… read more here.
Keywords: chemical bond; machine learning; materials chemical; interatomic potentials ... See more keywords