Journal
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
Volume 11, Issue 2, Pages -Publisher
WILEY
DOI: 10.1002/wcms.1491
Keywords
databases; density functional theory; machine learning; high-throughput computing; quantum chemistry
Funding
- Division of Advanced Cyberinfrastructure [1449723, 1547580]
- Office of Science [17-SC-20-SC]
- Open Force Field Consortium
Ask authors/readers for more resources
The QCArchive project by MolSSI includes a central server and Python-based software infrastructure for quantum chemistry computation and data storage. Users can access millions of QC computations for free and mine the data easily through web applications. The open-source software infrastructure also supports independent computation and distribution of vast QC calculations.
The Molecular Sciences Software Institute's (MolSSI) Quantum Chemistry Archive (QCArchive) project is an umbrella name that covers both a central server hosted by MolSSI for community data and the Python-based software infrastructure that powers automated computation and storage of quantum chemistry (QC) results. The MolSSI-hosted central server provides the computational molecular sciences community a location to freely access tens of millions of QC computations for machine learning, methodology assessment, force-field fitting, and more through a Python interface. Facile, user-friendly mining of the centrally archived quantum chemical data also can be achieved through web applications found at . The software infrastructure can be used as a standalone platform to compute, structure, and distribute hundreds of millions of QC computations for individuals or groups of researchers at any scale. The QCArchiveInfrastructureis open-source (BSD-3C), code repositories can be found at , and releases can be downloaded via PyPI and Conda. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry Data Science > Computer Algorithms and Programming
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available