ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
AI-Driven TENGs for Self-Powered Smart Sensors and Intelligent Devices.
Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Self-powered intelligence for personalized healthcare.National science review · 2026Review
- Self-Powered Bearing Sensing and Real-Time Fault Diagnosis Enabled by Non-Invasive Triboelectric Sensors and Edge AI Acceleration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Self-Powered Ultrastretchable Microstructured Intelligent Sensing Technology Based on Tactile Perception of Limb Movement.ACS omega · 2026Article
- Next-generation smart ophthalmic biomaterials: From passive response to active interaction and closed-loop control.Bioactive materials · 2026Review
- Three Key Aspects of Electron Transfer Behavior in Single-Electrode Triboelectric Nanogenerators for Sensing Optimization.Sensors (Basel, Switzerland) · 2025Article
- AI-Integrated Micro/Nanorobots for Biomedical Applications: Recent Advances in Design, Fabrication, and Functions.Biosensors · 2025Review
- Deep Learning-Assisted Fingerprint-Inspired Flexible Pressure Sensor for Tension Monitoring in Carbon Fiber Production.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Energy Storage, Power Management, and Applications of Triboelectric Nanogenerators for Self-Powered Systems: A Review.Micromachines · 2025Review
- Polymer Gel-Based Triboelectric Nanogenerators: Conductivity and Morphology Engineering for Advanced Sensing Applications.Gels (Basel, Switzerland) · 2025Review
- AI-Driven TENGs for Self-Powered Smart Sensors and Intelligent Devices.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Triboelectric nanogenerators (TENGs) are emerging as transformative technologies for sustainable energy harvesting and precision sensing, offering eco-friendly power generation from mechanical motion. They harness mechanical energy while enabling self-sustaining sensing for self-powered devices. However, challenges such as material optimization, fabrication techniques, design strategies, and output stability must be addressed to fully realize their practical potential. Artificial intelligence (AI), with its capabilities in advanced data analysis, pattern recognition, and adaptive responses, is revolutionizing fields like healthcare, industrial automation, and smart infrastructure. When integrated with TENGs, AI can overcome current limitations by enhancing output, stability, and adaptability. This review explores the synergistic potential of AI-driven TENG systems, from optimizing materials and fabrication to embedding machine learning and deep learning algorithms for intelligent real-time sensing. These advancements enable improved energy harvesting, predictive maintenance, and dynamic performance optimization, making TENGs more practical across industries. The review also identifies key challenges and future research directions, including the development of low-power AI algorithms, sustainable materials, hybrid energy systems, and robust security protocols for AI-enhanced TENG solutions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.