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ScaleLat: A chemical structure matching algorithm for mapping atomic structure of multi-phase system and high entropy alloys

  • Nan Li
  • , Haoliang Liu
  • , Sateng Li
  • , Junming Guo
  • , Qianwu Li
  • , Fangjie Shi
  • , Yefei Li
  • , Bing Xiao
  • Xi'an Jiaotong University
  • Suzhou Nuclear Power Research Institute

科研成果: 期刊稿件 › 文章 › 同行评审

2 引用 (Scopus)

摘要

ScaleLat (Scale Lattice) is a computer program written in C for performing the atomic structure analysis of multi-phase system or high entropy alloys (HEAs). The program implements an atomic cluster cell extraction algorithm to obtain all symmetry independent characteristic atomic cluster cells for the complex atomic configurations which are usually obtained from molecular dynamics or kinetic Monte-Carlo simulations at nanoscale or mesoscopic scale. ScaleLat implements an efficient and unique chemical structure matching algorithm to match all extracted atomic clusters from a large supercell (>104 atoms) to a representative small one (∼ 103 or less), providing the possibility to directly use the highly accurate quantum mechanical methods to study the electronic, magnetic, and mechanical properties of multi-component alloys for complex microstructures. We demonstrate the capability of ScaleLat code by conducting both the atomic structure matching analysis for Fe-12.8 at.% Cr binary alloy and equiatomic CrFeCoNiCu high entropy alloy, successfully obtaining the representative supercells containing 102∼103 atoms for two systems. The reliability of the proposed chemical structure matching scheme is tested and confirmed by calculating the electronic structures of both examples using trial supercells with various sizes. Overall, ScaleLat program provides a universal platform to efficiently map all essential chemical structures of large complex atomic structures to a relatively easy-handling small supercell for quantum mechanical calculations of various user interested properties.

源语言英语
期刊论文编号109265
期刊Computer Physics Communications
卷303
DOI
出版状态已出版 - 10月 2024

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