Shuaibin Wan

PhD candidate
Department of Mechanical and Aerospace Engineering
The Hong Kong University of Science and Technology
Email: swanad [at] connect [dot] ust [dot] hk

Google Scholar / ResearchGate / Linkedin

About me

I am a PhD candidate at The Hong Kong University of Science and Technology. My research lies in the intersection of machine learning and energy storage devices, aiming to optimize battery performance with machine intelligence.

Education

• The Hong Kong Univerisity of Science and Technology 2018 - Present
  Ph.D. (ongoing), Mechanical and Aerospace Engineering
• Harbin Institute of Technology 2014 - 2018
  B.Eng., Material Science and Engineering

Publications

• Shuaibin Wan*, Haoran Jiang*, Zixiao Guo, Changxiang He, Xiongwei Liang, Djilali Ned, and Tianshou Zhao. Machine learning-assisted design of flow fields for redox flow batteries. Energy & Environmental Scicence 15, 2874-2888 (2022). (Front Cover)
• Shuaibin Wan*, Xiongwei Liang*, Haoran Jiang, Jing Sun, Ned Djilali, and Tianshou Zhao. A coupled machine learning and genetic algorithm approach to the design of porous electrodes for redox flow batteries. Applied Energy 298, 117177 (2021).
• Jiahui Xu, Shuaibin Wan, Yao Wang, Su Huang, Zhihao Yuan, Fanglin Chen, Yanxiang Zhang, and Tong Liu. Enhancing performance of molybdenum doped strontium ferrite electrode by surface modification through Ni infiltration. International Journal of Hydrogen Energy 46 (18), 10876-10891 (2021).
• Guang Jiang, Fuyao Yan, Shuaibin Wan, Yanxiang Zhang, and Mufu Yan. Microstructure evolution and kinetics of B-site nanoparticle exsolution from an A-site-deficient perovskite surface: a phase-field modeling and simulation study. Physical Chemistry Chemical Physics 21 (21), 10902-10907 (2019).
• Shuaibin Wan, Mufu Yan, and Yanxiang Zhang. A numerical study of infiltrated solid oxide fuel cell electrode with dual‐phase backbone. International Journal of Energy Research 43 (7), 2562-2570 (2019).
  * Equal contribution