Choice of Efficiency and Economy: The Role of Machine Learning in Advancing Battery Technologies
Year: 2025
Type: article
Abstract: With the growth in global energy demands and the prominent need for sustainable development, battery technology has attracted significant attention as a crucial means of energy storage. Applying machine learning in battery technology offers new avenues for enhancing battery performance, safety, and lifespan. Through a literature review, this study comprehensively analyses the current status of machine learning in battery capacity prediction, solid electrolyte research and new material screening. It also explores the related research achievements, existing problems and future development directions, emphasising the importance of high-quality data, appropriate model selection, strict validation and interdisciplinary collaboration in promoting the progress of battery technology.
Author: Fangzhou Xu
Institution: National University of Singapore
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4407827835