JARVIS_QMOF

The JARVIS_QMOF dataset is part of the joint automated repository for various integrated simulations (JARVIS) database. This dataset contains configurations from the Quantum Metal-Organic Frameworks (QMOF) dataset, comprising quantum-chemical properties for >14,000 experimentally synthesized MOFs...

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Bibliographische Detailangaben
Hauptverfasser:	Rosen, Andrew S., Shaelyn M. Iyer, Debmalya Ray, Zhenpeng Yao, Alán Aspuru-Guzik, Gagliardi, Laura, Notestein, Justin M., Snurr, Randall Q.
Format:	Dataset
Sprache:	eng
Schlagworte:	AgPd_NPJ_2021 ColabFit Dataset https://id.loc.gov/authorities/subjects/sh85079324.html https://id.loc.gov/authorities/subjects/sh85082094.html Machine Learning Materials Science Research Areas/Atomic & molecular structure/Potential energy surfaces Research Areas/Electronic structure/Interatomic & molecular potentials Techniques/Computational Techniques/First-principles calculations Techniques/Computational Techniques/Machine Learning Techniques/Computational Techniques/Molecular Dynamics
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Beschreibung
Zusammenfassung:	The JARVIS_QMOF dataset is part of the joint automated repository for various integrated simulations (JARVIS) database. This dataset contains configurations from the Quantum Metal-Organic Frameworks (QMOF) dataset, comprising quantum-chemical properties for >14,000 experimentally synthesized MOFs. QMOF contains "DFT-ready" data: filtered to remove omitted, overlapping, unbonded or deleted atoms, along with other kinds of problematic structures commented on in the literature. Data were generated via high-throughput DFT workflow, at the PBE-D3(BJ) level of theory using VASP software. JARVIS is a set of tools and collected datasets built to meet current materials design challenges.
DOI:	10.60732/67cd629a