This Title All WIREs
How to cite this WIREs title:
WIREs Comput Mol Sci
Impact Factor: 25.113

The MolSSI QCArchive project: An open‐source platform to compute, organize, and share quantum chemistry data

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract 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 https://qcarchive.molssi.org. 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 QCArchive Infrastructure is open‐source (BSD‐3C), code repositories can be found at https://github.com/MolSSI, 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
The full QCArchive Infrastructure and how each layer and module communicates. Between different locations, all pieces communicate over TCP/IP protocols; within individual boxes, all pieces are connected through a single Python interpreter; and between a resource task queue and workers, communication can come in a variety of RPC sockets over either MPI or local Ethernet
[ Normal View | Magnified View ]
A Jupyter notebook demonstrating pulling a water geometry from the PubChem database52 and computing both Q‐Chem and Psi4 with the same input. Note the difference in absolute energies is primarily due to the fact that Q‐Chem uses direct SCF algorithms by default while Psi4 uses density‐fitting
[ Normal View | Magnified View ]
A Jupyter notebook showing a molecule object created from an XYZ string, the O‐H distance (Bohr) and HOH angle (degrees) measured, and the computation of a conversion factor for a gradient
[ Normal View | Magnified View ]
Relationship between the QCArchive project, MolSSI, and the CMS community
[ Normal View | Magnified View ]
An example of the Reaction Datasets Viewer app showing the S22 dataset under several DFT method and basis combinations
[ Normal View | Magnified View ]
An example of the Quantum Chemistry Machine Learning Datasets Repository showing an expansion of the COMP6 DrugBank dataset
[ Normal View | Magnified View ]
Visualization of the butane carbon backbone torsion using the TorsionDrive Dataset object to compare several methods
[ Normal View | Magnified View ]
Setup and evaluation of a force field, machine learning potential, and DFT computations with a TorsionDrive Dataset object
[ Normal View | Magnified View ]
An example setup for a new TorsionDrive Dataset object with hydrogen peroxide and butane molecules
[ Normal View | Magnified View ]
An image showing QCPortal pulling the S22 dataset from the MQCAS, listing all current B3LYP interaction energies, and rendering an example molecular complex from the dataset
[ Normal View | Magnified View ]

Browse by Topic

Computer and Information Science > Computer Algorithms and Programming
Software > Quantum Chemistry
Electronic Structure Theory > Ab Initio Electronic Structure Methods

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts