TY - JOUR
T1 - From Mining to Manufacturing
T2 - Scientific Challenges and Opportunities behind Battery Production
AU - Xiao, Jie
AU - Cao, Xia
AU - Gridley, Bernard
AU - Golden, William
AU - Ji, Yuchen
AU - Johnson, Stacey
AU - Lu, Dongping
AU - Lin, Feng
AU - Liu, Jun
AU - Liu, Yijin
AU - Liu, Zhao
AU - Ramesh, Hemanth Neelgund
AU - Shi, Feifei
AU - Schrooten, Jeremy
AU - Sims, Mary J.
AU - Sun, Shijing
AU - Shao, Yuyan
AU - Vaisman, Alon
AU - Yang, Jihui
AU - Whittingham, M. Stanley
N1 - Publisher Copyright:
© 2025 The Authors. Published by American Chemical Society.
PY - 2025/7/9
Y1 - 2025/7/9
N2 - This Review explores the status and progress made over the past decade in the areas of raw material mining, battery materials and components scale-up, processing, and manufacturing. While substantial advancements have been achieved in understanding battery materials, the transition to large-scale manufacturing introduces scientific challenges that must be addressed from multiple perspectives. Rather than focusing on new material discoveries or incremental performance improvements, this Review focuses on the critical issues that arise in battery manufacturing and highlights the importance of cost-oriented fundamental research to bridge the knowledge gap between fundamental research and industrial production. Challenges and opportunities in integrating machine learning (ML) and artificial intelligence (AI) to digitalize the manufacturing process and eventually realize fully autonomous production are discussed. The review also emphasizes the pressing need for workforce development to meet the growing demands of the battery industry. Potential strategies are suggested for accelerating the manufacturing of current and future battery technologies, ensuring that the workforce is equipped with the necessary skills to support research, development, and large-scale production.
AB - This Review explores the status and progress made over the past decade in the areas of raw material mining, battery materials and components scale-up, processing, and manufacturing. While substantial advancements have been achieved in understanding battery materials, the transition to large-scale manufacturing introduces scientific challenges that must be addressed from multiple perspectives. Rather than focusing on new material discoveries or incremental performance improvements, this Review focuses on the critical issues that arise in battery manufacturing and highlights the importance of cost-oriented fundamental research to bridge the knowledge gap between fundamental research and industrial production. Challenges and opportunities in integrating machine learning (ML) and artificial intelligence (AI) to digitalize the manufacturing process and eventually realize fully autonomous production are discussed. The review also emphasizes the pressing need for workforce development to meet the growing demands of the battery industry. Potential strategies are suggested for accelerating the manufacturing of current and future battery technologies, ensuring that the workforce is equipped with the necessary skills to support research, development, and large-scale production.
UR - https://www.scopus.com/pages/publications/105003303732
U2 - 10.1021/acs.chemrev.4c00980
DO - 10.1021/acs.chemrev.4c00980
M3 - Review article
C2 - 40261670
AN - SCOPUS:105003303732
SN - 0009-2665
VL - 125
SP - 6397
EP - 6431
JO - Chemical Reviews
JF - Chemical Reviews
IS - 13
ER -