Artificial Intelligence Applied to Battery Research: Hype or Reality?

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.

Automated summary

This article is a critical review of the application of artificial intelligence/machine learning methods in battery research. It aims to provide a comprehensive and authoritative review that is easily understandable to the battery community. The review discusses the concepts, approaches, tools, outcomes, and challenges of using AI/ML to accelerate the design and optimization of the next generation of batteries, and intends to make these tools accessible to the chemistry and electrochemical energy sciences communities while covering various aspects of battery R&D.