Papers citing Applying Machine Learning to Rechargeable Batteries: From the Microscale to the Macroscale
Early Degradation Trajectory Prediction of Lithium-ion Batteries Based on Degradation Pattern Recognition
SSRN Electronic Journal · 2026-01-01
Fu Wan, 朱寿龙, Yupeng Lin, De Yang, Jingyi Mu, Ruiqi Liu, Wenwei Yin, Weigen Chen
Read original paper ↗ ·Machine learning interatomic potential enables interface-level insights into cathode/solid electrolyte adhesion in sodium-ion batteries
Journal of Energy Storage · 2026-02-27
Woojin Shin, Kyoungmin Min
Read original paper ↗ ·Battery Capacity Estimation Across Vehicles with Heterogeneous Features Based on Variational Encoder-Long Short-Term Memory Network
Journal of Physics Conference Series · 2026-04-01
Zhexin Zhang, Linjing Zhang, Lintao Hou, Caiping Zhang
Read original paper ↗ ·Nanoscale Room-Temperature Na Dynamics in Layered Ruthenates Na1RuO3 and Na1.5RuO3
Nanomaterials · 2026-05-08
M. Hussein N. Assadi
Read original paper ↗ ·Machine learning-assisted health management of retired batteries
Journal of Energy Chemistry · 2026-09-01
Yuchen Xu, Jinxuan Chen, Tianxiang Zeng, Weiwen Peng, Ruohan Guo, Jinpeng Tian, C.Y. Chung
Read original paper ↗ ·Fluorinated Gel Polymer Electrolytes for Lithium Metal Batteries: From Passive Protection to Adaptive Interfacial Regulation
Advanced Materials · 2026-09-16
Min Wang, Yijing Liu, Mengjie Li, Yunshan Zheng, Cuiping Han, Baohua Li
Read original paper ↗ ·