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Development of interatomic potential for Al–Tb alloys using a deep neural network learning method

Ling Tang, Zhenqing Yang, Tongqi Wen, Kai‐Ming Ho, Matt Kramer, Cai‐Zhuang Wang

2020Physical Chemistry Chemical Physics52 citationsDOIOpen Access PDF

Abstract

liquid and the undercooled liquid is also analyzed and three dominant SROs, i.e., Al-centered distorted icosahedron (DISICO) and Tb-centered '3661' and '15551' clusters, respectively, are identified.

Topics & Concepts

Interatomic potentialArtificial neural networkDeep learningMaterials scienceArtificial intelligenceNanotechnologyComputer scienceChemistryMolecular dynamicsComputational chemistryMachine Learning in Materials ScienceThermodynamic and Structural Properties of Metals and AlloysX-ray Diffraction in Crystallography
Development of interatomic potential for Al–Tb alloys using a deep neural network learning method | Litcius