Leaf surface-microstructure inspired fabrication of fish gelatin-based triboelectric nanogenerator

Xuewen Shi, Yuewen Wei, Ren Yan, Lixuan Hu, Jiacai Zhi, Biao Tang, Yijia Li, Zhuoqi Yao, Chuanqian Shi, Hai Dong Yu, Wei Huang

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

Triboelectric nanogenerators (TENGs) are promising for energy harvesting and self-powered sensing due to their small size, portability, and great potential to convert mechanical energy into electrical energy output. The structural design for the surfaces of friction pairs can efficiently improve the output performance of TENGs. However, current strategies for fabricating such surface structures are usually cumbersome, expensive, and/or eco-unfriendly. In this work, we report green fabrication of fish gelatin-based TENG (FG-TENG) inspired by the surface microstructures of natural leaves, which has low cost, superior performance, and good degradability. Leaves from four common plants with different microstructures were selected to modify the surface structures of friction pairs to achieve a performance gain in power generation. It is found that the friction pairs that mimics the pyramidal microstructures on the surface of the lotus leaf has the highest power generation performance. The voltage and current performance of leaf microstructure-inspired FG-TENG (LMFG-TENG) increases up to 5.8 and 3.8 times, with the maximum voltage of ∼320 V and the current of ∼0.80 μA. Furthermore, the LMFG-TENG exhibits excellent electrical stability, which can maintain electric output under ten thousand cyclic tests. Such LMFG-TENG has been not only used for energy harvest and power supply, but also used for self-powered sensing. This work provides a green and natural surface modification method of friction materials for enhancing the power generation of nanogenerators.

Original languageEnglish
Article number108231
JournalNano Energy
Volume109
DOIs
StatePublished - May 2023

Keywords

  • Energy harvesting
  • Fish gelatin
  • Leaf microstructure
  • Self-powered sensing
  • Triboelectric nanogenerator

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