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
Accessing negative Poisson’s ratio of graphene by machine learning interatomic potentials
Sign Up to like & getrecommendations! Published in 2022 at "Nanotechnology"
DOI: 10.1088/1361-6528/ac5cfd
Abstract: The negative Poisson’s ratio (NPR) is a novel property of materials, which enhances the mechanical feature and creates a wide range of application prospects in lots of fields, such as aerospace, electronics, medicine, etc. Fundamental… read more here.
Keywords: graphene; negative poisson; machine learning; poisson ratio ... See more keywords
Molecular dynamics study on magnesium hydride nanoclusters with machine-learning interatomic potential
Sign Up to like & getrecommendations! Published in 2020 at "Physical Review B"
DOI: 10.1103/physrevb.102.094111
Abstract: We introduce a machine-learning (ML) interatomic potential for Mg-H system based on Behler-Parrinello approach. In order to fit the complex bonding conditions in the cluster structure, we combine multiple sampling strategies to obtain training samples… read more here.
Keywords: interatomic potential; mathrm; molecular dynamics; machine learning ... See more keywords
Evaluation of Machine Learning Interatomic Potentials for the Properties of Gold Nanoparticles
Sign Up to like & getrecommendations! Published in 2022 at "Nanomaterials"
DOI: 10.3390/nano12213891
Abstract: We have investigated Machine Learning Interatomic Potentials in application to the properties of gold nanoparticles through the DeePMD package, using data generated with the ab-initio VASP program. Benchmarking was carried out on Au20 nanoclusters against… read more here.
Keywords: interatomic potentials; gold nanoparticles; machine; machine learning ... See more keywords