Literature DB >> 29847095

Air-Flow-Driven Triboelectric Nanogenerators for Self-Powered Real-Time Respiratory Monitoring.

Meng Wang1, Jiahao Zhang1, Yingjie Tang1, Jun Li2, Baosen Zhang1, Erjun Liang1, Yanchao Mao1, Xudong Wang2.   

Abstract

Respiration is one of the most important vital signs of humans, and respiratory monitoring plays an important role in physical health management. A low-cost and convenient real-time respiratory monitoring system is extremely desirable. In this work, we demonstrated an air-flow-driven triboelectric nanogenerator (TENG) for self-powered real-time respiratory monitoring by converting mechanical energy of human respiration into electric output signals. The operation of the TENG was based on the air-flow-driven vibration of a flexible nanostructured polytetrafluoroethylene (n-PTFE) thin film in an acrylic tube. This TENG can generate distinct real-time electric signals when exposed to the air flow from different breath behaviors. It was also found that the accumulative charge transferred in breath sensing corresponds well to the total volume of air exchanged during the respiration process. Based on this TENG device, an intelligent wireless respiratory monitoring and alert system was further developed, which used the TENG signal to directly trigger a wireless alarm or dial a cell phone to provide timely alerts in response to breath behavior changes. This research offers a promising solution for developing self-powered real-time respiratory monitoring devices.

Entities:  

Keywords:  PTFE; mechanical energy harvesting; respiration monitoring; self-powered electronics; triboelectric nanogenerator

Mesh:

Substances:

Year:  2018        PMID: 29847095      PMCID: PMC6279609          DOI: 10.1021/acsnano.8b02562

Source DB:  PubMed          Journal:  ACS Nano        ISSN: 1936-0851            Impact factor:   15.881


  13 in total

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9.  An Optimized Flutter-Driven Triboelectric Nanogenerator with a Low Cut-In Wind Speed.

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Review 10.  Respiration-driven triboelectric nanogenerators for biomedical applications.

Authors:  Jun Li; Yin Long; Fan Yang; Xudong Wang
Journal:  EcoMat       Date:  2020-08-09
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