aflow++: A C++ framework for autonomous materials design
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.
Duke Scholars
Altmetric Attention Stats
Dimensions Citation Stats
Published In
DOI
ISSN
Publication Date
Volume
Related Subject Headings
- Materials
- 5104 Condensed matter physics
- 4016 Materials engineering
- 0912 Materials Engineering
- 0205 Optical Physics
- 0204 Condensed Matter Physics
Citation
Published In
DOI
ISSN
Publication Date
Volume
Related Subject Headings
- Materials
- 5104 Condensed matter physics
- 4016 Materials engineering
- 0912 Materials Engineering
- 0205 Optical Physics
- 0204 Condensed Matter Physics