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AI-Driven TENGs for Self-Powered Smart Sensors and Intelligent Devices
Aiswarya Baburaj1, Syamini Jayadevan2, Akshaya Kumar Aliyana2
1Department of Electronics, Mangalore University, Mangalore, 574199, India.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|April 25, 2025
Summary
Artificial intelligence (AI) enhances triboelectric nanogenerators (TENGs) for sustainable energy harvesting and sensing. AI integration optimizes TENG performance, stability, and adaptability for broader industrial applications.
Area of Science:
- Materials Science
- Energy Harvesting
- Artificial Intelligence
Background:
- Triboelectric nanogenerators (TENGs) offer eco-friendly energy harvesting from mechanical motion.
- Current TENGs face challenges in material optimization, fabrication, design, and output stability.
- Artificial intelligence (AI) excels in data analysis, pattern recognition, and adaptive responses.
Purpose of the Study:
- To explore the synergistic potential of AI-driven TENG systems.
- To review advancements in AI for optimizing TENG materials, fabrication, and performance.
- To identify challenges and future research directions for AI-enhanced TENGs.
Main Methods:
- Review of existing literature on AI and TENG integration.
- Analysis of AI techniques (machine learning, deep learning) applied to TENGs.
- Identification of AI-driven strategies for TENG optimization and intelligent sensing.
Main Results:
- AI integration enhances TENG output, stability, and adaptability.
- AI enables intelligent real-time sensing and predictive maintenance.
- AI-driven TENGs show improved practicality across various industries.
Conclusions:
- AI and TENG synergy holds significant potential for advanced energy harvesting and sensing.
- Future research should focus on low-power AI, sustainable materials, hybrid systems, and security.
- AI-enhanced TENGs are poised to become more practical and versatile in industrial applications.
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