Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal–Organic Framework Database: CoRE MOF 2019
Open accessAbstract
Over 14 000 porous, three-dimensional metal–organic framework structures are compiled and analyzed as a part of an update to the Computation-Ready, Experimental Metal–Organic Framework Database (CoRE MOF Database). The updated database includes additional structures that were contributed by CoRE MOF users, obtained from updates of the Cambridge Structural Database and a Web of Science search, and derived through semiautomated reconstruction of disordered structures using a topology-based crystal generator. In addition, value is added to the CoRE MOF database through new analyses that can speed up future nanoporous materials discovery activities, including open metal site detection and duplicate searches. Crystal structures (only for the subset that underwent significant changes during curation), pore analytics, and physical property data are included with the publicly available CoRE MOF 2019 database.
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Chung et al. refined a subset of the CSD believed to contain porous MOFs in CoRE-MOF, which has been updated recently to contain more than 14,000 MOFs.
“Chung et al. (29) have refined a subset of the CSD believed to contain porous MOFs in a set known as the computationready experimental MOF data set (i.e., CoRE-MOF), which has been updated recently to contain more than 14,000 MOFs.”
From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [29]
Experimental data sets do not necessarily have the same characteristics as hypothetical sets.
“It has been observed (40) that experimental data sets [e.g., of MOFs in CoRE-MOF (29)] also do not necessarily have the same characteristics as hypothetical sets [e.g., hMOF (27) or ToBaCCo (28)].”
From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [29]
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- Authors
- Chung, Y. G., Haldoupis, E., Bucior, B. J., Haranczyk, M., Lee, S., Zhang, H., Vogiatzis, K. D., Milisavljevic, M., Ling, S., Camp, J. S., Slater, B., Siepmann, J. I., Sholl, D. S., & Snurr, R. Q.
- Affiliations
- Pusan National University (KR)
- University of Minnesota (US)
- Northwestern University (US)
- IMDEA Materials Institute , C/Eric Kandel 2 , , ,
- Georgia Institute of Technology (US)
- University of Nottingham (GB)
- University College London (GB)
- Corresponding author
- Chung, Yongchul G.
- Siepmann, J. Ilja
- Sholl, David S.
- Snurr, Randall Q.
- ORCID
- Venue
- Journal of Chemical & Engineering Data
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-11-04
- Volume
- 64
- Issue
- 12
- Pages
- 5985-5998
- ISSN
- 0021-9568 (ISSN-L)
- 1520-5134
- OpenAlex
- W2983028326
- Cited by
- 863
- References
- 72
- Citations by year
- 2026: 130 · 2025: 180 · 2024: 175 · 2023: 122 · 2022: 96 · 2021: 89 · 2020: 66 · 2019: 5
- FWCI
- 23.94
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Chemical & Engineering Data (publishedVersion, other-oa)
- Repository@Nottingham (University of Nottingham) (acceptedVersion, other-oa)
- Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- Division of Graduate Education (DGE-1324585)
- Basic Energy Sciences (DE-FG02-12ER16362, DE-FG02-17ER16362)
- National Research Foundation of Korea (2016R1D1A1B03934484)
- Topics
- Physical Sciences › Chemistry › Inorganic Chemistry › Metal-Organic Frameworks: Synthesis and Applications
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Physical Sciences › Materials Science › Materials Chemistry › Covalent Organic Framework Applications
- Keywords
- metal-organic frameworks, crystal structure database, nanoporous materials, open metal sites, physical properties, Cambridge Structural Database
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