aflow++: a C++ framework for autonomous materials design

作     者：Oses, Corey Esters, Marco Hicks, David Divilov, Simon Eckert, Hagen Friedrich, Rico Mehl, Michael J. Smolyanyuk, Andriy Campilongo, Xiomara van de Walle, Axel Schroers, Jan Kusne, A. Gilad Takeuchi, Ichiro Zurek, Eva Nardelli, Marco Buongiorno Fornari, Marco Lederer, Yoav Levy, Ohad Toher, Cormac Curtarolo, Stefano 

作者机构：Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Center for Autonomous Materials Design Duke University DurhamNC27708 United States LIFT American Lightweight Materials Manufacturing Innovation Institute DetroitMI48216 United States Institute of Ion Beam Physics and Materials Research Helmholtz-Zentrum Dresden-Rossendorf Dresden01328 Germany Theoretical Chemistry Technische Universität Dresden Dresden01062 Germany Institute of Solid State Physics Technische Universität Wien WienA-1040 Austria School of Engineering Brown University ProvidenceRI02912 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06511 United States Materials Measurement Science Division National Institute of Standards and Technology GaithersburgMD20899 United States Department of Materials Science and Engineering University of Maryland College ParkMD20742 United States Department of Chemistry State University of New York at Buffalo BuffaloNY14260 United States Department of Physics Department of Chemistry University of North Texas DentonTX76203 United States Santa Fe Institute Santa FeNM87501 United States Department of Physics Science of Advanced Materials Program Central Michigan University Mount PleasantMI48859 United States Department of Physics NRCN P.O. Box 9001 Beer-Sheva84190 Israel Department of Materials Science and Engineering Department of Chemistry and Biochemistry University of Texas at Dallas RichardsonTX75080 United States 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2022年

核心收录：

主　　题：Quality assurance 

摘      要：The realization of novel technological opportunities given by computational and autonomous materials design requires efficient and effective frameworks. For more than two decades, aflow++ (Automatic-Flow Framework for Materials Discovery) has provided an interconnected collection of algorithms and workflows to address this challenge. This article contains an overview of the software and some of its most heavily-used functionalities, including algorithmic details, standards, and examples. Key thrusts are highlighted: the calculation of structural, electronic, thermodynamic, and thermomechanical properties in addition to the modeling of complex materials, such as high-entropy ceramics and bulk metallic glasses. The aflow++ software prioritizes interoperability, minimizing the number of independent parameters and tolerances. It ensures consistency of results across property sets — facilitating machine learning studies. The software also features various validation schemes, offering real-time quality assurance for data generated in a high-throughput fashion. Altogether, these considerations contribute to the development of large and reliable materials databases that can ultimately deliver future materials systems. © 2022, CC BY.