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Dual-Tunable Memristor Based on Carbon Nanotubes and Graphene Quantum Dots

Nanocarbon materials have the advantages of biocompatibility, thermal stability and chemical stability and have shown excellent electrical properties in electronic devices. In this study, Al/MWCNT:GQD/ITO memristors with rewritable nonvolatile properties were prepared based on composites consisting...

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Detalles Bibliográficos
Autores principales: Wang, Lu, Yang, Jing, Zhang, Yukai, Wen, Dianzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8401814/
https://www.ncbi.nlm.nih.gov/pubmed/34443874
http://dx.doi.org/10.3390/nano11082043
Descripción
Sumario:Nanocarbon materials have the advantages of biocompatibility, thermal stability and chemical stability and have shown excellent electrical properties in electronic devices. In this study, Al/MWCNT:GQD/ITO memristors with rewritable nonvolatile properties were prepared based on composites consisting of multiwalled carbon nanotubes (MWCNTs) and graphene quantum dots (GQDs). The switching current ratio of such a device can be tuned in two ways. Due to the ultraviolet light sensitivity of GQDs, when the dielectric material is illuminated by ultraviolet light, the charge capture ability of the GQDs decreases with an increasing duration of illumination, and the switching current ratio of the device also decreases with an increasing illumination duration (10(3)–10). By exploiting the charge capture characteristics of GQDs, the trap capture level can be increased by increasing the content of GQDs in the dielectric layer. The switching current ratio of the device increases with increasing GQD content (10–10(3)). The device can be programmed and erased more than 100 times; the programmable switching state can withstand 10(5) read pulses, and the retention time is more than 10(4) s. This memristor has a simple structure, low power consumption, and enormous application potential for data storage, artificial intelligence, image processing, artificial neural networks, and other applications.