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Advanced Studies on Hydrogen Energy Using Computational Chemistry

Advanced Studies on Hydrogen Energy Using Computational Chemistry
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Author(s): Devanshi Srivastava (Harcourt Butler Technical University, India)and Adarsh Kumar Arya (Harcourt Butler Technical University, India)
Copyright: 2025
Pages: 24
Source title: Practical Applications of Machine Learning and AI: Medicine, Environmental Science, Transportation, and Education
Source Author(s)/Editor(s): Toufik Mzili (Chouaib Doukkali University, Morocco)and Adarsh Kumar Arya (Harcourt Butler Technical University, India)
DOI: 10.4018/979-8-3373-1399-3.ch007

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Abstract

The paper examines the latest optimization models for the hydrogen transportation and production. Optimization plays a crucial role in systematic methodologies that aid in hydrogen expansion. Energy for most systems comes from non-renewable sources like fossil fuels, which take a long time to recharge and never quite reach their full potential. Energy problems, climate change, and environmental degradation have all resulted from the widespread usage of fossil fuels. One of the many benefits of hydrogen is its abundance of clean, efficient sources. In order to back up hydrogen expansion, systematic techniques must include optimization. Some of the recent developments in the transportation, storage, and generation of hydrogen are covered, including the use of clean processes such as photo electrolysis, water electrolysis, pyrolysis, and partial oxidation. Researchers interested in applying optimization approaches to hydrogen supply chain networks may find this study to be a useful blueprint.

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