The MAterials Simulation Toolkit (MAST) for atomistic modeling of defects and diffusion

被引：30

作者：

Mayeshiba, Tam ^{[1
]}

Wu, Henry ^{[1
]}

Angsten, Thomas ^{[1
,2
]}

Kaczmarowski, Amy ^{[1
,3
]}

Song, Zhewen ^{[1
]}

Jenness, Glen ^{[1
,4
]}

Xie, Wei ^{[1
,2
]}

Morgan, Dane ^{[1
]}

机构：

[1] Univ Wisconsin, Dept Mat Sci & Engn, 1509 Univ Ave, Madison, WI 53706 USA

[2] Univ Calif Berkeley, Dept Mat Sci & Engn, 210 Hearst Min Bldg, Berkeley, CA 94720 USA

[3] Sandia Natl Labs, Albuquerque, NM 87185 USA

[4] Univ Delaware, Catalysis Ctr Energy Innovat, 221 Acad St, Newark, DE 19716 USA

来源：

COMPUTATIONAL MATERIALS SCIENCE | 2017年 / 126卷

基金：

美国国家科学基金会;

关键词：

Ab-initio; Defect; Diffusion; DFT; Atomic; Simulation; ELASTIC BAND METHOD; OXYGEN MIGRATION; INITIO;

D O I：

10.1016/j.commatsci.2016.09.018

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The MAterials Simulation Toolkit (MAST) is a workflow manager and post-processing tool for ab initio defect and diffusion workflows. MAST codifies research knowledge and best practices for such workflows, and allows for the generation and management of easily modified and reproducible workflows, where data is stored along with workflow information for data provenance tracking. MAST is available for down-load through the Python Package Index, or at https://pypi.python.orgipypi/MAST, with installation instructions and a detailed user's guide at http://pythonhosted.org/MAST. MAST code may be browsed at the GitHub repository at https://github.com/uw-cmg/MAST. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：90 / 102

页数：13

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