Recent advances in piezoelectric and triboelectric self-powered sensors for human-machine interface applications DOI
Lei Du,

Yulong Li,

Ruizhe Qiu

и другие.

Journal of Micromechanics and Microengineering, Год журнала: 2024, Номер 34(9), С. 093001 - 093001

Опубликована: Июль 25, 2024

Abstract The burgeoning internet of things and artificial intelligence technologies have prospered a variety emerging applications. Human–machine interfaces (HMIs), for instance, enables users with intuitive, efficient, friendly way to interact machines, capable instant information acquisition, processing, communication, feedback, etc. These features require ultra-compact high-performance transducers, therefore self-powered sensors become the key underlying technology HMI This review focuses on piezoelectric, triboelectric, hybrid particular attention their microstructures fabrication methods, showing that both traditional microfabrication methods like three-dimensional (3D) printing, electrospinning, braiding contributed planar, array, porous, fabric, composite type sensors. Moreover, integration method piezoelectric triboelectric sensor arrays is investigated. crosstalk issue highlighted, i.e. signal interference between adjacent sensing units, current solutions such as array design optimization, processing improvement, material innovation reduce sensitivity been reviewed through specific examples. Three categories applications outlined, including intelligent interaction, robotics, human monitoring, detailed explanations how support these Through discussion challenges prospects, it proposed further coordinating micro devices HMIs will potentially boost application even higher level diversification, convenience, interconnectivity.

Язык: Английский

An Overview of Flame‐Retardant Materials for Triboelectric Nanogenerators and Future Applications DOI Creative Commons
Swati Panda, Sugato Hajra,

Hyeong-Geun Kim

и другие.

Advanced Materials, Год журнала: 2025, Номер unknown

Опубликована: Янв. 21, 2025

Abstract Triboelectric nanogenerators (TENGs) have gained significant attention for ability to convert mechanical energy into electrical energy. As the applications of TENG devices expand, their safety and reliability becomes priority, particularly where there is risk fire or spontaneous combustion. Flame‐retardant materials can be employed address these concerns without compromising performance efficiency TENGs. The primary focus this review on flame‐retardant materials, including polymers, biomaterials, liquid aerogels, carbon‐based materials. fundamental properties are elucidated. characteristics each material type described, along with potential boost importance flame retardancy in advancing technology projected from its usage wearable electronics, self‐powered sensors, smart textiles. Current challenges such as compatibility, fabrication complexity, environmental addressed, proposed strategies overcoming them. This underscores significance strengthening functionality devices, paving way widespread adoption across various industries.

Язык: Английский

Процитировано

4
Innovative Smart Gloves with Phalanges-based Triboelectric Sensors as a Dexterous Teaching Interface for Embodied Artificial Intelligence DOI
Long Liu, Tong Hu,

Xinmao Zhao

и другие.

Nano Energy, Год журнала: 2024, Номер unknown, С. 110491 - 110491

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

7
Flexible Organic Molecular Single Crystal-Based Triboelectric Device as a Self-Powered Tactile Sensor DOI
Parvati Marandi,

Dalip Saini,

Kiran Arora

и другие.

Journal of the American Chemical Society, Год журнала: 2024, Номер 146(38), С. 26178 - 26186

Опубликована: Сен. 16, 2024

Triboelectric nanogenerators (TENGs) have proven to be effective at converting mechanical energy into electrical power, making them a viable technology for operating self-powered electronic devices used in medical diagnostics and environmental monitoring. In the present study, we demonstrate utility of flexible single crystals an organic compound fabrication TENG as tactile sensor. Triboelectrification was attained result surface functionalization with positively negatively charged moieties, viz. Zn

Язык: Английский

Процитировано

6
Triboelectric Nanogenerator-Based Flexible Acoustic Sensor for Speech Recognition DOI
Yang Dai, Yunlong Li,

Shixian Xuan

и другие.

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

Опубликована: Фев. 6, 2025

The way people interact with machines through flexible acoustic sensors is revolutionizing the we live. However, developing a human-machine interaction sensor that simultaneously offers low cost, high stability, fidelity, and sensitivity remains significant challenge. In this study, based on sound-driven triboelectric nanogenerator was proposed. A poly(vinylidene fluoride) (PVDF)/graphene oxide (GO) composite nanofiber film obtained as dielectric layer electrospinning, copper-nickel alloy conductive fabric used electrode. An imitation embroidery shed structure designed in shape of ring to secure upper lower electrodes whole. Due porosity electrode, large contact area layer, stability structure, achieves 4.76 V·Pa-1 frequency response range 20-2000 Hz. multilayer attention convolutional network (MLACN) for speech recognition. recognition system achieved 99.5% accuracy rate recognizing common word pronunciations. integration nanogenerator-based deep learning techniques holds great promise field interaction.

Язык: Английский

Процитировано

0
Mechanical structure design: A survey on modern triboelectric nanogenerators DOI

Mina Nazarian-Samani,

Sima A. Alidokht, Héloïse Thérien‐Aubin

и другие.

Applied Energy, Год журнала: 2025, Номер 391, С. 125918 - 125918

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
Self‐Learning e‐Skin Respirometer for Pulmonary Disease Detection DOI Creative Commons
Anand Babu,

Getnet Kassahun,

Isabelle Dufour

и другие.

Advanced Sensor Research, Год журнала: 2024, Номер 3(12)

Опубликована: Июнь 16, 2024

Abstract Amid the landscape of respiratory health, lung disorders stand out as primary contributors to pulmonary intricacies and diseases. Timely precautions through accurate diagnosis hold key mitigating their impact. Nevertheless, existing conventional methods lungs monitoring exhibit limitations due bulky instruments, intrusive techniques, manual data recording, discomfort in continuous measurements. In this context, an unintrusive organic wearable piezoelectric electronic‐skin respirometer (eSR) exhibiting a high‐sensitivity (385 mV N −1 ), precise conversion factor (12 mL high signal‐to‐noise ratio (58 dB), low limit detection down 100 is demonstrated, which perfectly suitable record diverse breathing signals. To empower eSR with early functionality, self‐learning capability further added by integrating machine learning algorithms. Among various tested algorithms, gradient boosting regression emerges most suitable, leveraging sequential model refinement achieve accuracy exceeding 95% chronic obstructive diseases (COPD). From conception validation, approach not only provides alternative pathway for tracking progression but also has replace conformable AI‐empowered respirometer.

Язык: Английский

Процитировано

2
Recent advances in piezoelectric and triboelectric self-powered sensors for human-machine interface applications DOI
Lei Du,

Yulong Li,

Ruizhe Qiu

и другие.

Journal of Micromechanics and Microengineering, Год журнала: 2024, Номер 34(9), С. 093001 - 093001

Опубликована: Июль 25, 2024

Abstract The burgeoning internet of things and artificial intelligence technologies have prospered a variety emerging applications. Human–machine interfaces (HMIs), for instance, enables users with intuitive, efficient, friendly way to interact machines, capable instant information acquisition, processing, communication, feedback, etc. These features require ultra-compact high-performance transducers, therefore self-powered sensors become the key underlying technology HMI This review focuses on piezoelectric, triboelectric, hybrid particular attention their microstructures fabrication methods, showing that both traditional microfabrication methods like three-dimensional (3D) printing, electrospinning, braiding contributed planar, array, porous, fabric, composite type sensors. Moreover, integration method piezoelectric triboelectric sensor arrays is investigated. crosstalk issue highlighted, i.e. signal interference between adjacent sensing units, current solutions such as array design optimization, processing improvement, material innovation reduce sensitivity been reviewed through specific examples. Three categories applications outlined, including intelligent interaction, robotics, human monitoring, detailed explanations how support these Through discussion challenges prospects, it proposed further coordinating micro devices HMIs will potentially boost application even higher level diversification, convenience, interconnectivity.

Язык: Английский

Процитировано

2