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  5. A Hydrophobic Self-Repairing Power Textile for Effective Water Droplet Energy Harvesting

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Article
en
2021

A Hydrophobic Self-Repairing Power Textile for Effective Water Droplet Energy Harvesting

0 Datasets

0 Files

en
2021
Vol 15 (11)
Vol. 15
DOI: 10.1021/acsnano.1c06985

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Cuiying Ye
Di Liu
Peng Xiao
+7 more

Abstract

Triboelectric nanogenerators (TENGs) are useful for harvesting clean and widely distributed water droplet energy with high efficiency. However, the commonly used polymer films in TENGs for water droplet energy harvesting have the disadvantages of poor breathability, poor skin affinity, and irreparable hydrophobicity, which greatly hinder their wearable uses. Here, we report an all-fabric TENG (F-TENG), which not only has good air permeability and hydrophobic self-repairing properties but also shows effective energy conversion efficiency. The hydrophobic surface composed of SiO2 nanoparticles and poly(vinylidenefluoride-co-hexafluoropropylene)/perfluorodecyltrichlorosilane (PVDF-HFP/FDTS) exhibits a static contact angle of 157° and displays excellent acid and alkali resistance. Because of its low glass transition temperature, PVDF-HFP can facilitate the movement of FDTS molecules to the surface layer under heating conditions, realizing hydrophobic self-repairing performance. Furthermore, with the optimized compositions and structure, the water droplet F-TENG shows 7-fold enhancement of output voltage compared with the conventional single-electrode mode TENG, and a total energy conversion efficiency of 2.9% is achieved. Therefore, the proposed F-TENG can be used in multifunctional wearable devices for raindrop energy harvesting.

How to cite this publication

Cuiying Ye, Di Liu, Peng Xiao, Yang Jiang, Renwei Cheng, Chuan Ning, Feifan Sheng, Yihan Zhang, Kai Dong, Zhong Lin Wang (2021). A Hydrophobic Self-Repairing Power Textile for Effective Water Droplet Energy Harvesting. , 15(11), DOI: https://doi.org/10.1021/acsnano.1c06985.

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Publication Details

Type

Article

Year

2021

Authors

10

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1021/acsnano.1c06985

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