The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
High-throughput screening of bimetallic catalysts enabled by machine learning
Abstract
We present a holistic machine-learning framework for rapid screening of bimetallic catalysts with the aid of the descriptor-based kinetic analysis.
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Cites
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Cited by
Tran, K., & Ulissi, Z. W. (2018) · Nature Catalysis · doi:10.1038/s41929-018-0142-1 · Cited by 920
Combining 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
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
Hart, G. L. W., Mueller, T., Toher, C., & Curtarolo, S. (2021) · Nature Reviews Materials · doi:10.1038/s41578-021-00340-w · Cited by 703
Theory-guided design of catalytic materials using scaling relationships and reactivity descriptors
Zhao, Z.-J., Liu, S., Zha, S., Cheng, D., Studt, F., Henkelman, G., & Gong, J. (2019) · Nature Reviews Materials · doi:10.1038/s41578-019-0152-x · Cited by 657
Metadata
- Authors
- Li, Z., Wang, S., Chin, W. S., Achenie, L. E., & Xin, H.
- Venue
- Journal of Materials Chemistry A
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2017
- Volume
- 5
- Issue
- 46
- Pages
- 24131-24138
- ISSN
- 2050-7488 (ISSN-L)
- 2050-7496
- OpenAlex
- W2760744264
- Cited by
- 359
- References
- 54
- FWCI
- 10.61
- Type
- journal article
- Language
- en
- Open access
- closed
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- Li, Z., Wang, S., Chin, W. S., Achenie, L. E., & Xin, H. (2017). High-throughput screening of bimetallic catalysts enabled by machine learning. Journal of Materials Chemistry A. https://doi.org/10.1039/c7ta01812f
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
