Artificial Intelligence Applied to Battery Research: Hype or Reality?
Review article, 2022
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.
Author
Teo Lombardo
Centre national de la recherche scientifique (CNRS)
University of Picardie Jules Verne
Marc Duquesnoy
Centre national de la recherche scientifique (CNRS)
University of Picardie Jules Verne
Hassna El-Bouysidy
Centre national de la recherche scientifique (CNRS)
University of Picardie Jules Verne
Fabian Årén
Chalmers, Physics, Materials Physics
Centre national de la recherche scientifique (CNRS)
Alfonso Gallo-Bueno
Basque Research and Technology Alliance (BRTA)
Centre national de la recherche scientifique (CNRS)
Peter Bjørn Jørgensen
Technical University of Denmark (DTU)
Centre national de la recherche scientifique (CNRS)
Arghya Bhowmik
Technical University of Denmark (DTU)
Centre national de la recherche scientifique (CNRS)
Arnaud Demortière
Centre national de la recherche scientifique (CNRS)
University of Picardie Jules Verne
Elixabete Ayerbe
Centre national de la recherche scientifique (CNRS)
Centro de Investigacion Tecnológica En Electroquimica
Francisco Alcaide
Centre national de la recherche scientifique (CNRS)
Centro de Investigacion Tecnológica En Electroquimica
Marine Reynaud
Centre national de la recherche scientifique (CNRS)
Basque Research and Technology Alliance (BRTA)
Javier Carrasco
Basque Research and Technology Alliance (BRTA)
Centre national de la recherche scientifique (CNRS)
Alexis Grimaud
Centre national de la recherche scientifique (CNRS)
Collège de France
Sorbonne University
Chao Zhang
Uppsala University
Centre national de la recherche scientifique (CNRS)
T. Vegge
Centre national de la recherche scientifique (CNRS)
Technical University of Denmark (DTU)
Patrik Johansson
Centre national de la recherche scientifique (CNRS)
Chalmers, Physics, Materials Physics
Alejandro A. Franco
Centre national de la recherche scientifique (CNRS)
University of Picardie Jules Verne
Institut Universitaire de France
Chemical Reviews
0009-2665 (ISSN) 1520-6890 (eISSN)
Vol. 122 12 10899 -10969Highly concentrated electrolytes
Swedish Energy Agency (39909-1), 2015-02-01 -- 2019-09-30.
Tillämpad AI för batteri F&U
VINNOVA (2020-02321), 2020-11-01 -- 2021-07-15.
Areas of Advance
Transport
Energy
Materials Science
Subject Categories
Design
Information Science
Information Systemes, Social aspects
DOI
10.1021/acs.chemrev.1c00108
PubMed
34529918