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  5. Ultrahigh-Current-Density Tribovoltaic Nanogenerators Based on Hydrogen Bond-Activated Flexible Organic Semiconductor Textiles

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Article
en
2025

Ultrahigh-Current-Density Tribovoltaic Nanogenerators Based on Hydrogen Bond-Activated Flexible Organic Semiconductor Textiles

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en
2025
DOI: 10.1021/acsnano.4c11010

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Guoxu Liu
Beibei Fan
Youchao Qi
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Abstract

The polymer-based triboelectric nanogenerator (TENG) has long grappled with the constraint of limited current density (CD), whereas semiconductor-based triboelectric nanogenerators, using the tribovoltaic effect, have shown promising potential for achieving high current density. This study introduces an effective solution─a direct current tribovoltaic nanogenerator with ultrahigh current density─founded on a flexible organic semiconductor textile activated by solvents. By introducing 95% ethyl alcohol, an ultrahigh current density of 8.75 A/m2 and peak power density of 1.07 W/m2 are demonstrated, marking a striking enhancement of 438-fold and 170-fold, respectively, in comparison to the friction surface without 95% ethyl alcohol. The activation mechanism is that the poly(vinyl alcohol) dissolution by solvents exposes more PEDOT:PSS, and the formation of hydrogen bonds with PSS– releases more active PEDOT+. This advancement finds practical utility, as evidenced by successful demonstrations involving cell phone charging and small motor propulsion. The breakthrough unveiled in this work presents vistas for the widespread application of flexible organic semiconductor textile-based tribovoltaic nanogenerators, offering exciting opportunities for biomechanical energy harvesting.

How to cite this publication

Guoxu Liu, Beibei Fan, Youchao Qi, Kai Han, Jie Cao, Xianpeng Fu, Zhaozheng Wang, Tianzhao Bu, Jianhua Zeng, Sicheng Dong, Likun Gong, Zhong Lin Wang, Chi Zhang (2025). Ultrahigh-Current-Density Tribovoltaic Nanogenerators Based on Hydrogen Bond-Activated Flexible Organic Semiconductor Textiles. , DOI: https://doi.org/10.1021/acsnano.4c11010.

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Publication Details

Type

Article

Year

2025

Authors

13

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1021/acsnano.4c11010

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