Issue 31, 2024

A self-powered droplet sensor based on a triboelectric nanogenerator toward the concentration of green tea polyphenols

Abstract

Self-powered liquid droplet sensors based on triboelectric nanogenerators have attracted extensive attention in the field of biochemical sensing applications. Numerous research studies have investigated the effects of factors such as molecular species, molecular concentration, molecular charge, and molecular dipole moment in solution on the output electrical signals of the sensor. In this study, we prepared a self-powered droplet sensor using conductive copper film tape, polytetrafluoroethylene, and conductive aluminum foil tape. The sensor can continuously output pulsed electrical signals with minimal environmental impact. In comparison with other types of sensors, this sensor boasts a rapid response time of 10 ms and excellent sensitivity. The relationship between the friction-induced output current and voltage of the droplets and the concentration of green tea polyphenols (GTPs) was studied using the self-powered liquid droplet sensor with five different green tea samples. It was found that GTPs were the main factor contributing to the changes in output electrical signals in green tea water droplets. Fluorescence spectroscopy was used to reveal that the magnitude of the output current was inversely proportional to the concentration of GTPs in green tea. These results demonstrate the potential application of self-powered liquid droplet sensors in biochemical sensing applications based on concentration-dependent output signals.

Graphical abstract: A self-powered droplet sensor based on a triboelectric nanogenerator toward the concentration of green tea polyphenols

Supplementary files

Article information

Article type
Paper
Submitted
25 Apr 2024
Accepted
24 Jun 2024
First published
11 Jul 2024

Nanoscale, 2024,16, 14784-14792

A self-powered droplet sensor based on a triboelectric nanogenerator toward the concentration of green tea polyphenols

G. Lin, C. Su, C. Bao, M. Zhang, C. Li and Y. Yang, Nanoscale, 2024, 16, 14784 DOI: 10.1039/D4NR01799D

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