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March 5, 2026ChemEngineering0 citationsOpen Access

Material-Based Hydrogen Storage Technologies and Machine Learning Integration Overview

Material-Based Hydrogen Storage Technologies: A Frontier Overview of Systems, Challenges, and Machine Learning Integration

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Authors

HHHaval Kukha HawezJKJaidon Jibi KurisinkalTATaimoor Asim

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Overview

This review explores hydrogen storage technologies and their challenges, highlighting machine learning's role in optimization.

Key Points

  • The aim is to review surface hydrogen storage technologies and their practical integration while assessing challenges and machine learning applications.
  • Reviewed various hydrogen storage technologies including metal hydrides, MOFs, LOHCs, and more.
  • Conducted comparative analysis on Technology Readiness Levels of different storage systems.
  • Highlighted practical integration and techno-economic assessment of technologies.
  • LOHCs and hydrides show the highest Technology Readiness Level.
  • MOFs and carbohydrate-based systems demonstrate high gravimetric potential but are currently expensive.
  • Challenges include thermal management and large-scale regeneration for deployment.

Cite This Study

Hawez et al. (2026) studied this question.

synapsesocial.com/papers/69a91d9bd6127c7a504c0910https://doi.org/10.3390/chemengineering10030034
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