The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Computation-Ready, Experimental Metal–Organic Frameworks: A Tool To Enable High-Throughput Screening of Nanoporous Crystals
Abstract
Experimentally refined crystal structures for metal–organic frameworks (MOFs) often include solvent molecules and partially occupied or disordered atoms. This creates a major impediment to applying high-throughput computational screening to MOFs. To address this problem, we have constructed a database of MOF structures that are derived from experimental data but are immediately suitable for molecular simulations. The computation-ready, experimental (CoRE) MOF database contains over 4700 porous structures with publically available atomic coordinates. Important physical and chemical properties including the surface area and pore dimensions are reported for these structures. To demonstrate the utility of the database, we performed grand canonical Monte Carlo simulations of methane adsorption on all structures in the CoRE MOF database. We investigated the structural properties of the CoRE MOFs that govern methane storage capacity and found that these relationships agree well with those derived recently from a large database of hypothetical MOFs.
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Cites
Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis
Ong, S. P., Richards, W. D., Jain, A., Hautier, G., Kocher, M., Cholia, S., Gunter, D., Chevrier, V. L., Persson, K. A., & Ceder, G. (2013) · Computational Materials Science · doi:10.1016/j.commatsci.2012.10.028 · Cited by 4,534
Large-scale screening of hypothetical metal–organic frameworks
Wilmer, C. E., Leaf, M., Lee, C. Y., Farha, O. K., Hauser, B. G., Hupp, J. T., & Snurr, R. Q. (2012) · Nature Chemistry · doi:10.1038/nchem.1192 · Cited by 1,439
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Cited by
Moghadam, P. Z., Li, A., Wiggin, S. B., Tao, A., Maloney, A. G. P., Wood, P. A., Ward, S. C., & Fairen-Jimenez, D. (2017) · Chemistry of Materials · doi:10.1021/acs.chemmater.7b00441 · Cited by 1,082
Chung, Y. G., Haldoupis, E., Bucior, B. J., Haranczyk, M., Lee, S., Zhang, H., Vogiatzis, K. D., Milisavljevic, M., Ling, S., Camp, J. S., et al. (2019) · Journal of Chemical & Engineering Data · doi:10.1021/acs.jced.9b00835 · Cited by 863
Self-citationCombining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
Keith, J. A., Vassilev-Galindo, V., Cheng, B., Chmiela, S., Gastegger, M., Müller, K.-R., & Tkatchenko, A. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00107 · Cited by 849
Best Practices for the Synthesis, Activation, and Characterization of Metal–Organic Frameworks
Howarth, A. J., Peters, A. W., Vermeulen, N. A., Wang, T. C., Hupp, J. T., & Farha, O. K. (2017) · Chemistry of Materials · doi:10.1021/acs.chemmater.6b02626 · Cited by 746
Self-citationUnderstanding the diversity of the metal-organic framework ecosystem
Moosavi, S. M., Nandy, A., Jablonka, K. M., Ongari, D., Janet, J. P., Boyd, P. G., Lee, Y., Smit, B., & Kulik, H. J. (2020) · Nature Communications · doi:10.1038/s41467-020-17755-8 · Cited by 622
Metadata
- Authors
- Chung, Y. G., Camp, J., Haranczyk, M., Sikora, B. J., Bury, W., Krungleviciute, V., Yildirim, T., Farha, O. K., Sholl, D. S., & Snurr, R. Q.
- Venue
- Chemistry of Materials
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-10-24
- Volume
- 26
- Issue
- 21
- Pages
- 6185-6192
- ISSN
- 0897-4756 (ISSN-L)
- 1520-5002
- OpenAlex
- W1963883777
- Cited by
- 743
- References
- 2
- FWCI
- 15.38
- Type
- journal article
- Language
- en
- Open access
- closed
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