Special Issue

Topic: Machine Learning for Development and Management in Rechargeable Batteries

A Special Issue of Journal of Materials Informatics

ISSN 2770-372X (Online)

Submission deadline: 31 May 2025

Guest Editor(s)

Prof. Tieling Zhang
School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong, Australia.
Dr. Jinpeng Tian
Department of Electrical and Electronic Engineering and Research Centre for Grid Modernization, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.

Special Issue Introduction

Rechargeable batteries, exemplified by lithium-ion batteries, are playing a pivotal role in contemporary power systems and the electrification of transportation. However, current batteries face significant challenges, including performance degradation and thermal runaway. The intricate materials design space, under-explored electrochemical reactions, and dynamic operating conditions present significant hurdles to developing new battery technologies or management strategies. Machine learning has emerged as an indispensable tool for addressing these challenges.

Here, we invite researchers and practitioners to contribute to our Special Issue focused on the intersection of machine learning and batteries. Topics of interest include, but are not limited to, the following applications of machine learning:

● Battery materials discovery and structure optimization;

● Battery modeling, state estimation, fault diagnosis, and lifetime prediction;

● Battery charging, balancing, and thermal management; 

● Second use and recycling of retired batteries. 


Machine learning, battery materials, battery management

Submission Deadline

31 May 2025

Submission Information

For Author Instructions, please refer to https://www.oaepublish.com/jmi/author_instructions
For Online Submission, please login at https://oaemesas.com/login?JournalId=JMI&SpecialIssueId=JMI2406131
Submission Deadline: 31 May 2025
Contacts: Linda Cui, Assistant Editor, Editor@jmijournal.com

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Journal of Materials Informatics
ISSN 2770-372X (Online)
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