Journal article
Artificial Intelligence Applied to Battery Research: Hype or Reality?
Université de Picardie Jules Verne1
ALISTORE-ERI European Research Institute2
Autonomous Materials Discovery, Department of Energy Conversion and Storage, Technical University of Denmark3
Department of Energy Conversion and Storage, Technical University of Denmark4
Research center on batteries and supercapacitors5
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.
| Language: | English |
|---|---|
| Publisher: | American Chemical Society |
| Year: | 2022 |
| Pages: | 10899-10969 |
| ISSN: | 15206890 and 00092665 |
| Types: | Journal article |
| DOI: | 10.1021/acs.chemrev.1c00108 |
| ORCIDs: | 0000-0001-7950-9077 , Bhowmik, Arghya , 0000-0002-4706-4592 , 0000-0002-0156-8701 , 0000-0003-3117-6933 , 0000-0002-9966-205X , 0000-0002-7167-0840 , Vegge, Tejs , 0000-0002-9907-117X and 0000-0001-7362-7849 |
