Featured Publications on Machine Learning
- C. Deng, A. Kim, and W. Lu, “A generic battery-cycling optimization framework with learned sampling and early stopping strategies,” Patterns, 3, 100531, 2022.
- B. Wu, B. Zhang, C. Deng, and W. Lu, “Physics-encoded deep learning in identifying battery parameters without direct knowledge of ground truth,” Applied Energy, 321, 119390, 2022.
- C. Deng, Y. Wang, C. Qin, Y. Fu, and W. Lu, “Self-directed online machine learning for topology optimization,” Nature Communications, 13, 388, 2022.
- J. Zhang and W. Lu, “Sparse data machine learning for battery health estimation and optimal design incorporating material characteristics,” Applied Energy, 307, 118165, 2021.
- T. Gao and W. Lu, “Machine learning toward advanced energy storage devices and systems,” iScience, 24, 101936, 2021.
- C. Deng, X. Ji, C. Rainey, J. Zhang, and W. Lu, “Integrating machine learning with human knowledge,” iScience, 23, 101656, 2020.
- T. Gao and Wei Lu, “Physical model and machine learning enabled electrolyte channel design for fast charging,” Journal of The Electrochemical Society, 167, 110519, 2020.
- B. Wu, S. Han, K.G. Shin, and W. Lu, “Application of artificial neural networks in design of lithium-ion batteries,” Journal of Power Sources, 395, 128-136, 2018.