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 -10969

Highly 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

More information

Latest update

5/26/2023