A core–shell fiber moisture-driven electric generator enabled by synergetic complex coacervation and built-in potential
Abstract Moisture-driven electricity generators (MEGs) have been extensively researched; however, high-performance flexible variants have seldom been demonstrated. Here we present a novel complex coacervation with built-in potential strategy for developing a high-performance uniaxial MEG, featuring...
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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-54442-4 |
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| Summary: | Abstract Moisture-driven electricity generators (MEGs) have been extensively researched; however, high-performance flexible variants have seldom been demonstrated. Here we present a novel complex coacervation with built-in potential strategy for developing a high-performance uniaxial MEG, featuring a core of poly(3,4-ethylenedioxythiophene) (PEDOT) with a built-in charge potential and a gel shell composed of poly(diallyldimethylammonium chloride) (PDDA) and sodium alginate (NaAlg) coacervate. The complex coacervation of two oppositely charged polyelectrolytes produces extra mobile carriers and free volume in the device; meanwhile, the PEDOT core’s surface charge significantly accelerates carrier diffusion. Consequently, the uniaxial fiber-based MEG demonstrates breakthrough performance, achieving an output voltage of up to 0.8 V, a maximum current density of 1.05 mA/cm2, and a power density of 184 μW/cm2 at 20% relative humidity. Moreover, the mechanical robustness is ensured for the PEDOT nanoribbon substrate without performance degradation even after 100,000 folding cycles, making it suitable for self-powered human interactive sensor and synapse. Notably, we have constructed the inaugural MEG-synapse self-powered device, with a fiber-based MEG successfully operating a synaptic memristor, thereby emulating autonomous human synapses linked with fibrous neurons. Overall, this work pioneers innovative design strategies and application scenarios for high-performance MEGs. |
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| ISSN: | 2041-1723 |