L-shaped cantilever beam piezoelectric energy harvester with frequency up-conversion for ultra-low-frequency rotating environments DOI
Pan Zhang, Wanrong Lin, Zhengqiu Xie

и другие.

Mechanical Systems and Signal Processing, Год журнала: 2024, Номер 225, С. 112281 - 112281

Опубликована: Дек. 30, 2024

Язык: Английский

Advanced flexible self-healing triboelectric nanogenerators for applications in complex environments DOI
Dake Xu, Zhimin Jing, Hong Wang

и другие.

Nanoscale, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

With the advent of smart era, demand for clean energy is rising, and flexible triboelectric nanogenerators (F-TENGs) based on elastomers have garnered significant attention. Based principles electrostatic induction coupling, F-TENGs can convert mechanical motion into electrical are widely utilized in wearable devices blue energy. offer a simple design, ease manufacturing, usage scenarios. However, several weaknesses still limit their development. For example, F-TENG materials cannot recover from fatigue damage prone to output performance degradation under frequent friction or complex external conditions, leading failure. To address these issues, researchers explored use self-healable polymer-based layers electrodes. This review will provide detailed summary key scientific technological challenges faced by harsh environments, including ambient, high low temperatures, humidity, strong acids bases. Furthermore, research progress addressing issues future development also be presented explored. paper aims valuable insights guidance in-depth broad applications TENGs.

Язык: Английский

Процитировано

1

Triboelectric Sensor with a Hierarchical Structure for Omnidirectional Adaptive Wind Speed and Wind Direction Sensing for Unmanned Aerial Vehicles DOI
Zhihong Wang, Kuankuan Wang, Yixin Liu

и другие.

ACS Applied Materials & Interfaces, Год журнала: 2025, Номер unknown

Опубликована: Апрель 11, 2025

Unmanned aerial vehicles (UAVs) have transformed sectors, such as agriculture and logistics, requiring accurate environmental sensing for optimal functionality. Among various factors, wind speed direction are vital to flight stability energy efficiency. However, existing UAV anemometer technologies face challenges, including large size, high power consumption, complex integration. In this study, a novel (WSD) sensor, referred WSD-TENG, is introduced based on the principles of triboelectric nanogenerators (TENGs). The WSD-TENG consists thin-film TENG integrated with vane detection disk-shaped monitoring direction. An extensive evaluation structural parameters output performance demonstrates its ability function across speeds from 2.6 30.0 m/s 5° resolution in direction, showing stability. exhibits linear relationship between voltage frequency, goodness fit 0.9995, proves strong long-term reliability. Additionally, testing under simulated conditions validates dependability settings. A WSD-TENG-compatible signal processing module has also been developed integration UAVs, enabling application practical operations.

Язык: Английский

Процитировано

0

Symbiotic energy paradigm for self-sustaining aerial robots DOI
Hao Wang, Lingji Kong, Zheng Fang

и другие.

Nature Reviews Electrical Engineering, Год журнала: 2025, Номер unknown

Опубликована: Апрель 17, 2025

Язык: Английский

Процитировано

0

Exploration of Advanced Applications of Triboelectric Nanogenerator-Based Self-Powered Sensors in the Era of Artificial Intelligence DOI Creative Commons

Yi‐Feng Su,

D.L. Yin,

Xinmao Zhao

и другие.

Sensors, Год журнала: 2025, Номер 25(8), С. 2520 - 2520

Опубликована: Апрель 17, 2025

The integration of Deep Learning with sensor technologies has significantly advanced the field intelligent sensing and decision making by enhancing perceptual capabilities delivering sophisticated data analysis processing functionalities. This review provides a comprehensive overview synergy between sensors, particular focus on applications triboelectric nanogenerator (TENG)-based self-powered sensors combined artificial intelligence (AI) algorithms. First, evolution is reviewed, highlighting advantages, limitations, application domains several classical models. Next, innovative in autonomous driving, wearable devices, Industrial Internet Things (IIoT) are discussed, emphasizing critical role neural networks precision capabilities. then delves into TENG-based introducing their mechanisms based contact electrification electrostatic induction, material selection strategies, novel structural designs, efficient energy conversion methods. algorithms showcased through groundbreaking motion recognition, smart healthcare, homes, human–machine interaction. Finally, future research directions outlined, including multimodal fusion, edge computing integration, brain-inspired neuromorphic computing, to expand robotics, space exploration, other high-tech fields. offers theoretical technical insights collaborative innovation technologies, paving way for development next-generation systems.

Язык: Английский

Процитировано

0

Deep learning-enhanced safety system for real-time in-situ blade damage monitoring in UAV using triboelectric sensor DOI
Zhipeng Pan, Kuankuan Wang, Yixin Liu

и другие.

Nano Energy, Год журнала: 2025, Номер unknown, С. 111063 - 111063

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

L-shaped cantilever beam piezoelectric energy harvester with frequency up-conversion for ultra-low-frequency rotating environments DOI
Pan Zhang, Wanrong Lin, Zhengqiu Xie

и другие.

Mechanical Systems and Signal Processing, Год журнала: 2024, Номер 225, С. 112281 - 112281

Опубликована: Дек. 30, 2024

Язык: Английский

Процитировано

2