Multifunctional respiration-driven triboelectric nanogenerator for self-powered detection of formaldehyde in exhaled gas and respiratory behavior. (November 2022)

• Record Type: Journal Article
• Authors: Wang, Dongyue; Zhang, Dongzhi; Chen, Xiaoya; Zhang, Hao; Tang, Mingcong; Wang, Jianghao
• Is Part Of: Nano energy. Volume 102(2022)
• Publication Date: 2022-11
• Subjects: Self-powered sensor -- Triboelectric nanogenerator -- Ti3C2TX MXene -- Formaldehyde sensor -- Respiratory monitoring; Nanoscience -- Periodicals; Nanotechnology -- Periodicals; Nanostructured materials -- Periodicals; Power resources -- Technological innovations -- Periodicals; Nanoscience; Nanostructured materials; Nanotechnology; Power resources -- Technological innovations; Periodicals; 621.042
• DOI: 10.1016/j.nanoen.2022.107711
• Languages: English
• ISSNs: 2211-2855

Abstract

Abstract: Self-powered sensing system has great application prospect in environmental detection and human health. In this work, a triboelectric nanogenerator (TENG) prepared by Ti3 C2 Tx MXene/amino-functionalized multi-walled carbon nanotubes (MXene/NH2 -MWCNTs) was designed for self-powered detection of exhaled gas and disease diagnosis. The TENG driven by respiration can be used as both a power source and a sensor for the self-powered system. MXene/NH2 -MWCNTs composite sensitive to formaldehyde gas act as both friction layer and electrode of the TENG. The peak-to-peak value of open-circuit voltage and output power from the TENG can reach up to 136 V and 27 μW, respectively. As a self-powered formaldehyde sensor, the device has excellent gas-sensing response (35% @ 5 ppm), low detection limit (10 ppb) and fast response/recovery time (51/57 s). In addition, the respiration-driven TENG can detect formaldehyde in the exhaled gas of smokers and identify respiratory types, which has potential application value in diagnosing diseases related to exhaled gas. Sampling tests were performed for a variety of respiratory types associated with different diseases. Different respiratory types can be identified by using support vector machine model, and the average prediction accuracy is 100%. Graphical Abstract: ga1 Highlights: A Ti3 C2 Tx MXene/amino-functionalized multi-walled carbon nanotubes-based triboelectric nanogenerator (TENG) driven by wind was fabricated. The TENG can be used for formaldehyde detection and has excellent gas-sensing performance. The respiration-driven TENG shows good application value for self-powered detection of exhaled gas and disease diagnosis.