AI-Driven Nanomaterial-Enabled Green Hydrogen Energy Systems for Smart and Resilient Cities

The transformation of urban energy systems is becoming increasingly urgent as cities face rising energy demands, carbon reduction goals, and resilience challenges. Green hydrogen, generated through renewable-powered electrolysis, offers an effective pathway toward the decarbonization of key urban sectors such as transport, industry, and buildings. Recent developments in nanomaterials have revolutionized hydrogen technologies by improving catalytic activity, energy efficiency, and durability across production, storage, and conversion processes. In parallel, artificial intelligence (AI) is reshaping the energy landscape through predictive analytics, real-time supervisory control, and intelligent optimization of distributed energy networks. Yet, despite progress in both fields, their integration within smart city systems remains at an early stage. The absence of unified frameworks linking nanoscale material innovation with AI-enabled management impedes the realization of digitally intelligent, hydrogen-based cities.

This Research Topic aims to advance the integration of AI and nanomaterial-enabled hydrogen energy systems for sustainable and resilient urban infrastructures. The primary objective is to align innovations at the material and digital levels to enable efficient hydrogen production, conversion, and utilization within city-scale networks. Researchers are encouraged to investigate advanced AI-driven system modeling, optimization algorithms for dynamic hydrogen grids, and nanomaterial improvements aimed at maximizing energy efficiency and minimizing costs. The initiative also seeks to encourage cross-disciplinary collaboration among scientists, engineers, AI specialists, and urban planners. Ultimately, the goal is to design adaptive, data-driven, and sustainable hydrogen infrastructures that enhance urban energy flexibility and support carbon-neutral smart city transitions.

To gather further insights across materials and digital technologies, we welcome articles addressing, but not limited to, the following themes:

- Nanostructured catalysts and membranes for hydrogen production and purification
- Advanced materials for hydrogen storage and transport in urban energy systems
- AI and machine learning for materials discovery and system optimization
- Digital twins, predictive analytics, and smart control of hydrogen-integrated networks
- Hydrogen-based microgrids, energy coupling, and sectoral integration in cities
- Techno-economic assessment, life-cycle analysis, and sustainability metrics
- Policy frameworks, safety, and scalability of AI-integrated hydrogen solutions
- Demonstration projects and real-world case studies for urban hydrogen deployment

Appendix: This Research Topic welcomes original research articles, review papers, perspectives, and case studies.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Review
• Technology and Code

Keywords: Artificial Intelligence in Energy Systems, Smart Cities and Urban Sustainability, Hydrogen Production and Storage Technologies., Green Hydrogen Energy Systems, Nanomaterials for Energy Applications

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.