Artificial Intelligence Applied to Battery Research: Hype or Reality?
2021
Lombardo, Teo | Duquesnoy, Marc | El-Bouysidy, Hassna | Årén, Fabian | Gallo-Bueno, Alfonso | Jørgensen, Peter Bjørn | Bhowmik, Arghya | Demortière, Arnaud | Ayerbe, Elixabete | Alcaide, Francisco | Reynaud, Marine | Carrasco, Javier | Grimaud, Alexis | Zhang, Chao | Vegge, Tejs | Johansson, Patrik | Franco, Alejandro A.
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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