AI-ML techniques for green hydrogen: A comprehensive review
Green hydrogen is a cleaner source to replace fossil-based fuels and is critical in the global shift toward energy production to combat climate change. This review of embedding artificial intelligence (AI) and machine learning (ML) in the value chain of green hydrogen outlines the significant potent...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2025-07-01
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| Series: | Next Energy |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949821X25000158 |
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| author | Mamta Motiramani Priyanshi Solanki Vidhi Patel Tamanna Talreja Nainsiben Patel Divya Chauhan Alok Kumar Singh |
| author_facet | Mamta Motiramani Priyanshi Solanki Vidhi Patel Tamanna Talreja Nainsiben Patel Divya Chauhan Alok Kumar Singh |
| author_sort | Mamta Motiramani |
| collection | DOAJ |
| description | Green hydrogen is a cleaner source to replace fossil-based fuels and is critical in the global shift toward energy production to combat climate change. This review of embedding artificial intelligence (AI) and machine learning (ML) in the value chain of green hydrogen outlines the significant potential for full transformation. These include optimizing the utilization of renewable sources of energy, improving electrolysis process, hydrogen storage in the salt cavern that has better condition, and smarter systems in distribution side with inexpensive logistics. In this, it nullifies leak risks and safeguards the safety operations with detection using AI. Consequently, it positions the paper emphasizing AI-ML approaches demonstrating significant advancements in efficiency and sustainability in green hydrogen technology. |
| format | Article |
| id | doaj-art-07bd9cebee5e45529aa54552b106b246 |
| institution | DOAJ |
| issn | 2949-821X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Next Energy |
| spelling | doaj-art-07bd9cebee5e45529aa54552b106b2462025-08-20T02:45:27ZengElsevierNext Energy2949-821X2025-07-01810025210.1016/j.nxener.2025.100252AI-ML techniques for green hydrogen: A comprehensive reviewMamta Motiramani0Priyanshi Solanki1Vidhi Patel2Tamanna Talreja3Nainsiben Patel4Divya Chauhan5Alok Kumar Singh6Department of Computer Science and Engineering, Adani University, Ahmedabad, Gujarat 382 421, IndiaDepartment of Computer Science and Engineering, Adani University, Ahmedabad, Gujarat 382 421, IndiaDepartment of Computer Science and Engineering, Adani University, Ahmedabad, Gujarat 382 421, IndiaDepartment of Computer Science and Engineering, Adani University, Ahmedabad, Gujarat 382 421, IndiaDepartment of Computer Science and Engineering, Adani University, Ahmedabad, Gujarat 382 421, IndiaDepartment of Information and Communication Technology, Adani Institute of Infrastructure Engineering, Ahmedabad, Gujarat 382 421, IndiaDepartment of Electrical Engineering, Adani University, Ahmedabad, Gujarat 382 421, India; Corresponding author.Green hydrogen is a cleaner source to replace fossil-based fuels and is critical in the global shift toward energy production to combat climate change. This review of embedding artificial intelligence (AI) and machine learning (ML) in the value chain of green hydrogen outlines the significant potential for full transformation. These include optimizing the utilization of renewable sources of energy, improving electrolysis process, hydrogen storage in the salt cavern that has better condition, and smarter systems in distribution side with inexpensive logistics. In this, it nullifies leak risks and safeguards the safety operations with detection using AI. Consequently, it positions the paper emphasizing AI-ML approaches demonstrating significant advancements in efficiency and sustainability in green hydrogen technology.http://www.sciencedirect.com/science/article/pii/S2949821X25000158Artificial intelligence-machine learningEnergy optimizationGreen hydrogenRenewable energySustainability |
| spellingShingle | Mamta Motiramani Priyanshi Solanki Vidhi Patel Tamanna Talreja Nainsiben Patel Divya Chauhan Alok Kumar Singh AI-ML techniques for green hydrogen: A comprehensive review Next Energy Artificial intelligence-machine learning Energy optimization Green hydrogen Renewable energy Sustainability |
| title | AI-ML techniques for green hydrogen: A comprehensive review |
| title_full | AI-ML techniques for green hydrogen: A comprehensive review |
| title_fullStr | AI-ML techniques for green hydrogen: A comprehensive review |
| title_full_unstemmed | AI-ML techniques for green hydrogen: A comprehensive review |
| title_short | AI-ML techniques for green hydrogen: A comprehensive review |
| title_sort | ai ml techniques for green hydrogen a comprehensive review |
| topic | Artificial intelligence-machine learning Energy optimization Green hydrogen Renewable energy Sustainability |
| url | http://www.sciencedirect.com/science/article/pii/S2949821X25000158 |
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