基于全织物材料的快速响应混合压电-摩擦电压力传感器,用于增强传感和发电

IF 16.8 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Su Bin Choi , Sushmitha Veeralingam , Tran Duc Khanh , Jun Sang Choi , Kampara Roopa Kishore , Seung-Boo Jung , Jong-Woong Kim
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引用次数: 0

摘要

本研究提出了一种混合电子压力传感器,该传感器集成了摩擦电和压电效应,使用尼龙6,6和聚偏氟乙烯(PVDF)织物嵌入MXene和MoS 2纳米片。混合摩擦电纳米发电机(TENG)设计解决了单机构传感器中能量收集效率和压力传感性能之间的基本权衡。利用摩擦电效应在低压下的高电压输出和压电效应对施加压力的线性响应,该传感器实现了高达150 kPa的宽传感范围,3.18 V/kPa的高灵敏度和0.38 ms的超快速响应时间。MXene纳米填料的掺入通过在聚合物基体内形成导电通路来增强电荷传输,而PVDF/MoS 2 /MXene (PMMX)层进一步改善了摩擦和压电响应。MXene的高电负性和MoS 2的压电性质有助于提高灵敏度和电荷转移效率。当在身体各个部位进行测试时,传感器可以有效地检测人体运动并支持能量收集。此外,与一维卷积神经网络(1D-CNN)的集成在手势分类中达到99.18%的准确率,显示了其在智能可穿戴应用中的潜力。通过结合高效率,快速响应,广泛的传感范围和机器学习兼容性,这种混合传感器为下一代柔性和可穿戴电子产品提供了多功能和可持续的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Rapid-response hybrid piezo-triboelectric pressure sensor using all-fabric materials for enhanced sensing and power generation

Rapid-response hybrid piezo-triboelectric pressure sensor using all-fabric materials for enhanced sensing and power generation
This study presents a hybrid electronic pressure sensor that integrates triboelectric and piezoelectric effects using nylon-6,6 and polyvinylidene fluoride (PVDF) fabrics embedded with MXene and MoS₂ nanosheets. The hybrid triboelectric nanogenerator (TENG) design addresses the fundamental trade-off between energy harvesting efficiency and pressure sensing performance found in single-mechanism sensors. By leveraging the high voltage output of the triboelectric effect at low pressures and the linear response of the piezoelectric effect to applied pressure, this sensor achieves a broad sensing range of up to 150 kPa, high sensitivity of 3.18 V/kPa, and an ultra-fast response time of 0.38 ms. The incorporation of MXene nanofillers enhances charge transport by forming conductive pathways within the polymer matrix, while the PVDF/MoS₂/MXene (PMMX) layer further improves frictional and piezoelectric responses. MXene’s high electronegativity and MoS₂’s piezoelectric properties contribute to increased sensitivity and charge transfer efficiency. When tested on various body parts, the sensor effectively detects human motion and supports energy harvesting. Furthermore, integration with a one-dimensional convolutional neural network (1D-CNN) achieves 99.18 % accuracy in gesture classification, demonstrating its potential for smart wearable applications. By combining high efficiency, rapid response, broad sensing range, and machine learning compatibility, this hybrid sensor provides a versatile and sustainable solution for next-generation flexible and wearable electronics.
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来源期刊
Nano Energy
Nano Energy CHEMISTRY, PHYSICAL-NANOSCIENCE & NANOTECHNOLOGY
CiteScore
30.30
自引率
7.40%
发文量
1207
审稿时长
23 days
期刊介绍: Nano Energy is a multidisciplinary, rapid-publication forum of original peer-reviewed contributions on the science and engineering of nanomaterials and nanodevices used in all forms of energy harvesting, conversion, storage, utilization and policy. Through its mixture of articles, reviews, communications, research news, and information on key developments, Nano Energy provides a comprehensive coverage of this exciting and dynamic field which joins nanoscience and nanotechnology with energy science. The journal is relevant to all those who are interested in nanomaterials solutions to the energy problem. Nano Energy publishes original experimental and theoretical research on all aspects of energy-related research which utilizes nanomaterials and nanotechnology. Manuscripts of four types are considered: review articles which inform readers of the latest research and advances in energy science; rapid communications which feature exciting research breakthroughs in the field; full-length articles which report comprehensive research developments; and news and opinions which comment on topical issues or express views on the developments in related fields.
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