高通量晶格动力学框架

IF 9.4 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Zhuoying Zhu, Junsoo Park, Hrushikesh Sahasrabuddhe, Alex M. Ganose, Rees Chang, John W. Lawson, Anubhav Jain
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引用次数: 0

摘要

我们开发了一种自动化高通量工作流程,用于从第一原理计算晶格动力学特性,包括由非谐性决定的特性。该流水线可自动计算来自扰动训练超级单元的原子间力常数(IFCs),最高可达 4 阶,并使用 IFCs 计算晶格热导率、热膨胀系数以及振动自由能和熵。它对动态不稳定化合物进行声子重正化,以获得有限温度下的真实有效声子光谱,并计算相关的自由能修正。方法和参数的选择兼顾了计算效率和结果的准确性,并通过收敛测试和与实验测量结果的比较进行评估。大规模部署该工作流程将促进材料发现工作,从而实现热电、接触材料、铁电、航空航天组件以及一般相图构建等功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A high-throughput framework for lattice dynamics

A high-throughput framework for lattice dynamics

We develop an automated high-throughput workflow for calculating lattice dynamical properties from first principles including those dictated by anharmonicity. The pipeline automatically computes interatomic force constants (IFCs) up to 4th order from perturbed training supercells, and uses the IFCs to calculate lattice thermal conductivity, coefficient of thermal expansion, and vibrational free energy and entropy. It performs phonon renormalization for dynamically unstable compounds to obtain real effective phonon spectra at finite temperatures and calculates the associated free energy corrections. The methods and parameters are chosen to balance computational efficiency and result accuracy, assessed through convergence testing and comparisons with experimental measurements. Deployment of this workflow at a large scale would facilitate materials discovery efforts toward functionalities including thermoelectrics, contact materials, ferroelectrics, aerospace components, as well as general phase diagram construction.

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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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