The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A hybrid organic-inorganic perovskite dataset
Open accessAbstract
Hybrid organic-inorganic perovskites (HOIPs) have been attracting a great deal of attention due to their versatility of electronic properties and fabrication methods. We prepare a dataset of 1,346 HOIPs, which features 16 organic cations, 3 group-IV cations and 4 halide anions. Using a combination of an atomic structure search method and density functional theory calculations, the optimized structures, the bandgap, the dielectric constant, and the relative energies of the HOIPs are uniformly prepared and validated by comparing with relevant experimental and/or theoretical data. We make the dataset available at Dryad Digital Repository, NoMaD Repository, and Khazana Repository (http://khazana.uconn.edu/), hoping that it could be useful for future data-mining efforts that can explore possible structure-property relationships and phenomenological models. Progressive extension of the dataset is expected as new organic cations become appropriate within the HOIP framework, and as additional properties are calculated for the new compounds found.
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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
Machine learning bandgaps of double perovskites
Pilania, G., Mannodi-Kanakkithodi, A., Uberuaga, B. P., Ramprasad, R., Gubernatis, J. E., & Lookman, T. (2016) · Scientific Reports · doi:10.1038/srep19375 · Cited by 518
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Cited by
Chiral-perovskite optoelectronics
Long, G., Sabatini, R., Saidaminov, M. I., Lakhwani, G., Rasmita, A., Liu, X., Sargent, E. H., & Gao, W. (2020) · Nature Reviews Materials · doi:10.1038/s41578-020-0181-5 · Cited by 909
Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning
Lu, S., Zhou, Q., Ouyang, Y., Guo, Y., Li, Q., & Wang, J. (2018) · Nature Communications · doi:10.1038/s41467-018-05761-w · Cited by 725
Polymer Genome: A Data-Powered Polymer Informatics Platform for Property Predictions
Kim, C., Chandrasekaran, A., Huan, T. D., Das, D., & Ramprasad, R. (2018) · The Journal of Physical Chemistry C · doi:10.1021/acs.jpcc.8b02913 · Cited by 513
Self-citationLi, J., Pradhan, B., Gaur, S., & Thomas, J. (2019) · Advanced Energy Materials · doi:10.1002/aenm.201901891 · Cited by 220
Robot-Accelerated Perovskite Investigation and Discovery
Li, Z., Najeeb, M. A., Alves, L., Sherman, A. Z., Shekar, V., Cruz Parrilla, P., Pendleton, I. M., Wang, W., Nega, P. W., Zeller, M., et al. (2020) · Chemistry of Materials · doi:10.1021/acs.chemmater.0c01153 · Cited by 187
Metadata
- Authors
- Kim, C., Huan, T. D., Krishnan, S., & Ramprasad, R.
- Venue
- Scientific Data
- Published
- 2017-05-09
- Volume
- 4
- Issue
- 1
- Pages
- 170057-170057
- ISSN
- 2052-4463 (ISSN-L)
- OpenAlex
- W2612591418
- Cited by
- 174
- References
- 2
- Type
- data paper
- Language
- en
- Open access
- gold
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