The global shift to sustainable energy necessitates advancements in material science, especially at the nanoscale level. The intersection of materials physics, nanotechnology, clean energy, and artificial intelligence (AI) has recently emerged as a significant area of scientific inquiry. AI-driven data analytics, machine learning (ML), and predictive modeling are now enabling unprecedented capabilities in the design, optimization, and real-time monitoring of functional nanomaterials. This integration has created an urgent demand for new platforms to disseminate cutting-edge discoveries in functional nanomaterials, AI-assisted materials design, and advanced processing methods.
This Research Topic aims to enhance the understanding of innovative strategies for addressing energy challenges via material innovation and AI-empowered modeling, while also examining the fundamental physics that dictate these materials' behavior in operational and extreme conditions, such as irradiation environments.
We invite contributions that consolidate recent advancements in the design, synthesis, AI-driven discovery, and application of functional nanomaterials for energy harvesting, storage, and conversion technologies. Emphasis will be placed on hybrid composite systems, micro/nanostructures, advanced thin-film coatings, and intelligent optimization frameworks that enhance device-level performance in supercapacitors, batteries, and energy harvesters, including piezoelectric, thermoelectric, photovoltaic, and triboelectric systems.
Topics of interest include, but are not limited to: • Hybrid nanocomposites • Thin-film technologies • MEMS/NEMS platforms • Smart coatings • Ion-beam and SHI irradiation-based material modification • Computational modeling and AI/ML-assisted materials design • Smart Nanomaterials: AI and Physics for Next-Generation Energy Conversion and Storage • Data-driven approaches for accelerated material discovery and scale-up • Digital twins for nanomaterials and energy conversion systems
Submissions are encouraged to focus on novel approaches that not only improve device-level performance but also embrace AI-powered models for efficient, scalable, and intelligent energy solutions.
We encourage Original Research, Reviews, Mini Reviews, and Perspectives providing experimental, theoretical, simulation-based, or AI-enabled insights. Interdisciplinary studies bridging physics, nanotechnology, AI, and energy materials science are especially welcome.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Mini Review
Opinion
Original Research
Perspective
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
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Mini Review
Opinion
Original Research
Perspective
Review
Technology and Code
Keywords: Functional nanomaterials, Hybrid nanocomposites, Thin films, MEMS/NEMS, Ion-beam/SHI irradiation effects, Smart coatings, surface engineering, Wearable energy devices, Energy storage systems, Thermoelectric and piezoelectric nanomaterials
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.
