Multilayered piezo-tribo hybrid nanogenerator integrated with machine learning for advanced sign language to speech system

IF 21.8 2区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Advanced Composites and Hybrid Materials Pub Date : 2025-07-15 DOI:10.1007/s42114-025-01386-y

Monunith Anithkumar, Asokan Poorani Sathya Prasanna, Nagamalleswara Rao Alluri, Thanjan Shaji Bincy, Kwi-Il Park, Sang-Jae Kim

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引用次数: 0

Abstract

Multilayer structured piezo-triboelectric hybrid nanogenerators (m-PT-HNG) are emerging as promising candidates for next-generation wearable sensors owing to their ability to harvest energy with high sensitivity and enhanced output. In this work, we report a reliable and sensitive multilayered intrinsic piezo-tribo hybrid nanogenerator (m-PT-HNG) based on a multilayer piezoelectric composite nanogenerator (m-PCNG) architecture combined with triboelectric functionality. The m-PCNG fabricated via parallelly connected multilayers demonstrate significant enhancement of output performance compared to single-layer PCNG. The ferroelectric, piezoelectric performance of Cu₂O-doped 0.3Ba_0.7Ca_0.3TiO₃-0.7BaSn_0.12Ti_0.88O₃ (BCST-0.01Cu₂O) ceramic fillers was systematically optimized by applying various piston loads (10 to 50 kN) and an electric field of 25 kV/cm. The resulting intrinsically coupled m-PT-HNG produces an instantaneous power density of 85.36 mW/m² at 200 MΩ. To demonstrate practical utility, a sign language recognition smart glove (SLR-SG) was developed integrating the five m-PT-HNGs, enabling accurate sign language classification through a machine learning algorithm and real-time sign language to speech conversion via a mobile application.

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集成机器学习的多层压电-摩擦混合纳米发电机用于高级手语语音系统

多层结构压电-摩擦电混合纳米发电机（m-PT-HNG）因其具有高灵敏度和高输出的能量收集能力而成为下一代可穿戴传感器的有希望的候选者。在这项工作中，我们基于多层压电复合纳米发电机（m-PCNG）结构结合摩擦电功能，报道了一种可靠且敏感的多层本禀压电-摩擦混合纳米发电机（m-PT-HNG）。与单层PCNG相比，通过并联多层制备的m-PCNG的输出性能显著提高。通过施加不同活塞载荷（10 ~ 50 kN）和25 kV/cm的电场，系统地优化了掺cu20的0.3Ba0.7Ca0.3TiO3-0.7BaSn0.12Ti0.88O3 （BCST-0.01Cu2O）陶瓷填料的铁电、压电性能。由此产生的本质耦合m-PT-HNG在200 MΩ下产生85.36 mW/m2的瞬时功率密度。为了演示实际用途，开发了一款集成了5个m- pt - hng的手语识别智能手套（SLR-SG），通过机器学习算法实现准确的手语分类，并通过移动应用程序实现实时手语到语音的转换。

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来源期刊

Advanced Composites and Hybrid Materials Multiple-

CiteScore

26.00

自引率

21.40%

发文量

185

期刊介绍： Advanced Composites and Hybrid Materials is a leading international journal that promotes interdisciplinary collaboration among materials scientists, engineers, chemists, biologists, and physicists working on composites, including nanocomposites. Our aim is to facilitate rapid scientific communication in this field. The journal publishes high-quality research on various aspects of composite materials, including materials design, surface and interface science/engineering, manufacturing, structure control, property design, device fabrication, and other applications. We also welcome simulation and modeling studies that are relevant to composites. Additionally, papers focusing on the relationship between fillers and the matrix are of particular interest. Our scope includes polymer, metal, and ceramic matrices, with a special emphasis on reviews and meta-analyses related to materials selection. We cover a wide range of topics, including transport properties, strategies for controlling interfaces and composition distribution, bottom-up assembly of nanocomposites, highly porous and high-density composites, electronic structure design, materials synergisms, and thermoelectric materials. Advanced Composites and Hybrid Materials follows a rigorous single-blind peer-review process to ensure the quality and integrity of the published work.