This repository hosts the Quantum MOF (QMOF) database. See the corresponding documentation for information on how to download other files and data.
If you use or wish to cite the QMOF Database, please refer to the following publications:
A.S. Rosen, S.M. Iyer, D. Ray, Z. Yao, A. Aspuru-Guzik, L. Gagliardi, J.M. Notestein, R.Q. Snurr. "Machine Learning the Quantum-Chemical Properties of Metal–Organic Frameworks for Accelerated Materials Discovery", Matter, 4, 1578-1597 (2021). DOI: 10.1016/j.matt.2021.02.015.
A.S. Rosen, V. Fung, P. Huck, C.T. O'Donnell, M.K. Horton, D.G. Truhlar, K.A. Persson, J.M. Notestein, R.Q. Snurr. "High-Throughput Predictions of Metal–Organic Framework Electronic Properties: Theoretical Challenges, Graph Neural Networks, and Data Exploration," npj Comput. Mat. (2022). DOI: 10.1038/s41524-022-00796-6.
Funding
National Defense Science and Engineering Graduate Fellowship
Nanoporous Materials Genome Center (DE-FG02-17ER16362)