Accelerating structure relaxation in chemically disordered materials with a chemistry-driven model

IF 11.9 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Liying An, Huan Ma, Jinjia Liu, Wenping Guo, Xiaodong Wen
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引用次数: 0

Abstract

Chemically disordered materials are widely utilized, yet establishing structure-property relationship remains challenging due to their vast configurational space. Identifying thermal accessible low energy configurations of these materials through standard ab initio calculations is computationally expensive for doping induced structure changes. In this work, we propose a straightforward algorithm to optimize random structures into ground state configurations by matching chemical subgraphs. This algorithm constructs harmonic potential with chemistry-driven parameterization, without relying on iterative training to accelerate the relaxation process. It can completely bypass the need for relaxation with ab initio calculations in rigid systems and reduce computational costs by 30% in flexible systems. Leveraging its exceptional structural relaxation capabilities, we have also developed a generalized workflow for screening low-energy structures in disordered materials, aimed at expediting the screening process and accelerating new material discovery.

Abstract Image

用化学驱动模型加速化学无序材料的结构松弛
化学无序材料被广泛应用,但由于其巨大的构型空间,建立结构-性能关系仍然是一个挑战。通过标准从头计算确定这些材料的热可及低能构型对于掺杂引起的结构变化是计算昂贵的。在这项工作中,我们提出了一种简单的算法,通过匹配化学子图来优化随机结构到基态配置。该算法采用化学驱动的参数化构造谐波势,不依赖迭代训练来加速松弛过程。它可以完全绕过在刚性系统中从头开始计算的松弛需求,并将柔性系统的计算成本降低30%。利用其特殊的结构松弛能力,我们还开发了一种通用的工作流程,用于筛选无序材料中的低能量结构,旨在加快筛选过程并加速新材料的发现。
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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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