AI

Featured Publications on Machine Learning

  1. C. Deng, A. Kim, and W. Lu, “A generic battery-cycling optimization framework with learned sampling and early stopping strategies,” Patterns, 3, 100531, 2022.
  2. 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.
  3. C. Deng, Y. Wang, C. Qin, Y. Fu, and W. Lu, “Self-directed online machine learning for topology optimization,” Nature Communications, 13, 388, 2022.
  4. J. Zhang and W. Lu, “Sparse data machine learning for battery health estimation and optimal design incorporating material characteristics,” Applied Energy, 307, 118165, 2021.
  5. T. Gao and W. Lu, “Machine learning toward advanced energy storage devices and systems,” iScience, 24, 101936, 2021.
  6. C. Deng, X. Ji, C. Rainey, J. Zhang, and W. Lu, “Integrating machine learning with human knowledge,” iScience, 23, 101656, 2020.
  7. 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.
  8. 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.