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Lu, Z., Wang, J., Wu, Y., Guo, X. and Xiao, W. (2022) Predicting Hydrogen Storage Capacity of V-Ti-Cr-Fe Alloy via Ensemble Machine Learning. Int. J. Hydrog. Energy, 47, 34583-34593. https://doi.org/10.1016/j.ijhydene.2022.08.050

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• TITLE: Properties of Ti-Based Hydrogen Storage Alloy

  AUTHORS: Rui Xu, Tao Cheng, Chaoyu Li, Xue Yang, Junfeng Rong

  KEYWORDS: Renewable Energy, Hydrogen Storage, Ti-Based Alloy, Machine Learning

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.12 No.3, March 29, 2024

  ABSTRACT: An efficient and safe hydrogen storage method is one of the important links for the large-scale development of hydrogen in the future. Because of its low price and simple design, Ti-based hydrogen storage alloys are considered to be suitable for practical applications. In this paper, we review the latest research on Ti-based hydrogen storage alloys. Firstly, the machine learning and density functional theory are introduced to provide theoretical guidance for the optimization of Ti-based hydrogen storage alloys. Then, in order to improve the hydrogen storage performance, we briefly introduce the research of AB type and AB2 type Ti-based alloys, focusing on doping elements and adaptive after treatment. Finally, suggestions for the future research and development of Ti-based hydrogen storage alloys are proposed.