AI-Empowered Wireless Power Transfer Technology and Electromagnetic Metamaterials
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".
Deadline for manuscript submissions: 20 October 2025 | Viewed by 43
Special Issue Editors
Interests: wireless power transfer technologies; electromagnetic and thermal field simulation of inductor devices; small- and medium-sized photovoltaic converters
Interests: wireless power transfer; low-frequency metamaterial
Special Issues, Collections and Topics in MDPI journals
Interests: high-efficiency/high-power density power converters; wireless power transfer system; MHz power supply module with wide bandgap devices; power supply for aeronautics; astronautics applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
AI-empowered wireless power transfer (WPT) technology is emerging as a pivotal area of research, driven by its potential to revolutionize the wireless industry. As the demand for convenient, reliable, and safe wireless power transfer continues to grow, WPT systems have garnered significant attention. However, despite the numerous advantages of WPT technology, challenges such as decreasing transfer efficiency with increasing distance and the inevitable generation of large electromagnetic fields (EMFs) in charging systems remain unresolved. Metamaterials, engineered composite materials or structures, have emerged as innovative solutions to address these limitations. Recent advancements in WPT systems have demonstrated their effectiveness in enhancing transfer efficiency and mitigating EMF-induced electromagnetic compatibility issues.
This Special Issue aims to explore innovative applications of AI in WPT systems, including electromagnetic compatibility in metamaterial-based WPT systems, the use of AI in optimizing the performance of metamaterial-based wireless power transfer systems, theoretical studies on metamaterial-based WPT systems, magnetic-inductive and resonant wave phenomena in WPT systems via metamaterials, programmable metamaterials and metasurfaces for WPT systems, and smart wireless power transfer (SWIPT) technologies based on information metamaterials and metasurfaces. By fostering interdisciplinary collaboration and knowledge sharing, this initiative seeks to drive the development and implementation of groundbreaking AI-driven WPT technologies.
Prof. Dr. Chunfang Wang
Dr. Cancan Rong
Prof. Dr. Hongbo Ma
Guest Editors
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Keywords
- wireless power transfer
- energy efficiency
- metasurfaces and metamaterials
- artificial intelligence
- Internet of Things
- EM wave manipulation
- electromagnetic compatibility
- flexible wireless energy harvesting
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