The DOI matches its Crossref record; 354 of the 354 references it cites were found in a registry or an index.
Artificial Intelligence Applied to Battery Research: Hype or Reality?
Open accessAbstract
This is a critical review of artificial intelligence/machine learning (AI/ML) methods applied to battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily understandable, review of general interest to the battery community. It addresses the concepts, approaches, tools, outcomes, and challenges of using AI/ML as an accelerator for the design and optimization of the next generation of batteries─a current hot topic. It intends to create both accessibility of these tools to the chemistry and electrochemical energy sciences communities and completeness in terms of the different battery R&D aspects covered.
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Cites
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Cited by
Self-Driving Laboratories for Chemistry and Materials Science
Tom, G., Schmid, S. P., Baird, S. G., Cao, Y., Darvish, K., Hao, H., Lo, S., Pablo-García, S., Rajaonson, E. M., Skreta, M., et al. (2024) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00055 · Cited by 707
Wu, Y., Hu, Q., Liang, H., Wang, A., Xu, H., Wang, L., & He, X. (2023) · Advanced Energy Materials · doi:10.1002/aenm.202300259 · Cited by 270
Battery Safety: Machine Learning-Based Prognostics
Zhao, J., Feng, X., Pang, Q., Fowler, M., Lian, Y., Ouyang, M., & Burke, A. F. (2024) · Progress in Energy and Combustion Science · doi:10.1016/j.pecs.2023.101142 · Cited by 216
Fu, S., Tao, S., Fan, H., He, K., Liu, X., Tao, Y., Zuo, J., Zhang, X., Wang, Y., & Sun, Y. (2024) · Applied Energy · doi:10.1016/j.apenergy.2023.121991 · Cited by 141
Nguyen, V. N., Tarełko, W., Sharma, P., El-Shafay, A. S., Chen, W.-H., Nguyen, P. Q. P., Nguyen, X. P., & Hoang, A. T. (2024) · Energy & Fuels · doi:10.1021/acs.energyfuels.3c04343 · Cited by 130
Metadata
- Authors
- Lombardo, T., Duquesnoy, M., El-Bouysidy, H., Årén, F., Gallo-Bueno, A., Jørgensen, P. B., Bhowmik, A., Demortière, A., Ayerbe, E., Alcaide, F., Reynaud, M., Carrasco, J., Grimaud, A., Zhang, C., Vegge, T., Johansson, P., & Franco, A. A.
- Venue
- Chemical Reviews
- Publisher
- American Chemical Society (ACS)
- Published
- 2021-09-16
- Volume
- 122
- Issue
- 12
- Pages
- 10899-10969
- ISSN
- 0009-2665 (ISSN-L)
- 1520-6890
- OpenAlex
- W3200695454
- Cited by
- 503
- References
- 354
- FWCI
- 3.40
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- The paper
- Lombardo, T., Duquesnoy, M., El-Bouysidy, H., Årén, F., Gallo-Bueno, A., Jørgensen, P. B., Bhowmik, A., Demortière, A., Ayerbe, E., Alcaide, F., Reynaud, M., Carrasco, J., Grimaud, A., Zhang, C., Vegge, T., Johansson, P., & Franco, A. A. (2022). Artificial Intelligence Applied to Battery Research: Hype or Reality? Chemical Reviews. https://doi.org/10.1021/acs.chemrev.1c00108
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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