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  5. Revealing the conductivity stability of 2D Cu-MOFs as flexible electrodes: demonstration of triboelectric nanogenerators

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Article
en
2023

Revealing the conductivity stability of 2D Cu-MOFs as flexible electrodes: demonstration of triboelectric nanogenerators

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en
2023
Vol 111
Vol. 111
DOI: 10.1016/j.nanoen.2023.108427

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Paul Kim Ho Chu
Paul Kim Ho Chu

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Yinghong Wu
Yang Luo
Paul Kim Ho Chu
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Abstract

Owing to the high electron delocalization in 2D ultrathin regions derived from π-d conjugations, electrically conductive metal-organic frameworks (MOFs) are widely used in electronic applications but mostly for rigid devices. The interaction mechanism between conductive 2D MOFs and flexible substrates remains unclear, which cannot meet the increasing demand for next-generation wearable electronics. Herein, conductive copper-benzenehexathiol (Cu-BHT) layers are developed and the underlying mechanisms responsible for the conductivity difference on different representative substrates are explored. It is found that not only the molecular movement inside the polymer but also the fusion between polymer and Cu-MOFs affects the intrinsic conductivity and long-term stability. Therefore, the potential guiding criteria for selecting flexible substrates for conductive 2D MOFs are established. As a demonstration, the Cu-BHT/polymer layer is considered the flexible electrode of triboelectric nanogenerators to harvest energy from water droplets and human motions, verifying the significant role of conductive 2D MOFs in flexible and wearable applications. This study reveals the insights to the potential interaction effect on the conductivity stability of Cu-BHT and advances the development of 2D conductive MOFs in flexible and wearable electronics.

How to cite this publication

Yinghong Wu, Yang Luo, Paul Kim Ho Chu, Carlo Menon (2023). Revealing the conductivity stability of 2D Cu-MOFs as flexible electrodes: demonstration of triboelectric nanogenerators. , 111, DOI: https://doi.org/10.1016/j.nanoen.2023.108427.

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Publication Details

Type

Article

Year

2023

Authors

4

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1016/j.nanoen.2023.108427

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