4.8 Article

Ligand-Triggered Self-Assembly of Flexible Carbon Dot Nanoribbons for Optoelectronic Memristor Devices and Neuromorphic Computing

Journal

ADVANCED SCIENCE
Volume 10, Issue 12, Pages -

Publisher

WILEY
DOI: 10.1002/advs.202207688

Keywords

2D nanoribbons; carbon dots; flexible electronic device; memristor; self-assembly

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Flexible carbon dot ribbons with excellent optical, electrical and semiconducting properties have been synthesized through efficient packing of individual carbon dots. These ribbons show outstanding stability and fast optoelectronic responses, making them ideal active layer materials for transparent flexible memristors with rapid Chinese character learning capability. This work lays the foundation for wearable artificial intelligence.
Carbon dots (CDs) are widely utilized in sensing, energy storage, and catalysis due to their excellent optical, electrical and semiconducting properties. However, attempts to optimize their optoelectronic performance through high-order manipulation have met with little success to date. In this study, through efficient packing of individual CDs in two-dimensions, the synthesis of flexible CDs ribbons is demonstrated technically. Electron microscopies and molecular dynamics simulations, show the assembly of CDs into ribbons results from the tripartite balance of pi-pi attractions, hydrogen bonding, and halogen bonding forces provided by the superficial ligands. The obtained ribbons are flexible and show excellent stability against UV irradiation and heating. CDs ribbons offer outstanding performance as active layer material in transparent flexible memristors, with the developed devices providing excellent data storage, retention capabilities, and fast optoelectronic responses. A memristor device with a thickness of 8 mu m shows good data retention capability even after 10(4) cycles of bending. Furthermore, the device functions effectively as a neuromorphic computing system with integrated storage and computation capabilities, with the response speed of the device being less than 5.5 ns. These properties create an optoelectronic memristor with rapid Chinese character learning capability. This work lays the foundation for wearable artificial intelligence.

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