Welcome to Francis Academic Press

Academic Journal of Materials & Chemistry, 2024, 5(2); doi: 10.25236/AJMC.2024.050204.

Transformation of Lithium Battery Material Design and Optimization Based on Artificial Intelligence

Author(s)

Gao Feng

Corresponding Author:
Gao Feng
Affiliation(s)

School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China

Abstract

This paper explores the methods of lithium battery material design and optimization based on artificial intelligence. Firstly, the current research status and challenges of lithium battery materials are introduced, followed by a discussion on the advantages of artificial intelligence in material design and optimization and specific algorithms. The paper then describes the process of lithium battery material design based on artificial intelligence, including material characteristics, data processing, algorithm selection, and result analysis. Furthermore, optimization methods for lithium battery materials and performance evaluation are discussed, along with exploration of future research directions. Through this study, new ideas and methods are provided for the design and optimization of lithium battery materials.

Keywords

Artificial Intelligence, Lithium Battery, Material Design, Optimization, Algorithm

Cite This Paper

Gao Feng. Transformation of Lithium Battery Material Design and Optimization Based on Artificial Intelligence. Academic Journal of Materials & Chemistry (2024) Vol. 5, Issue 2: 18-22. https://doi.org/10.25236/AJMC.2024.050204.

References

[1] Lian, Yue. Optimization Design of Niobium Oxide Anode Materials and Study on Lithium Storage Behavior [D]. Yangzhou University, 2024.

[2] Zhang, Furen, Gou, Huan, Liang, Beibei, et al. Optimization Design of Heat Dissipation Performance for Composite Thermal Management System of Lithium Battery [J]. Journal of Chongqing Jiaotong University (Natural Science Edition), 2023, 42(04): 145-152.

[3] Lu, Yanbing. Optimization Design and Heat Transfer Performance Study of Microchannel Cold Plate for Lithium Ion Battery [D]. Harbin Institute of Technology, 2022. DOI: 10.27061/d.cnki. ghgdu. 2022. 002767. 

[4] Hou, Xiankun. Design and Performance Optimization of Sodium-Based Dual-Ion Battery Materials [D]. Northeast Normal University, 2021.