Affiliations 

  • 1 Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China. Zhao_zw@seu.edu.cn
  • 2 State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology Chinese Academy of Sciences, Nanjing 210008, People's Republic of China
  • 3 Institute of Nanoscience and Nanotechnology, University Putra Malaysia, Serdang, Selangor, Malaysia
  • 4 Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai 200241, People's Republic of China
Mater Horiz, 2023 Jun 06;10(6):2181-2190.
PMID: 36994553 DOI: 10.1039/d3mh00117b

Abstract

As an emerging carbon-based material, carbon quantum dots (CQDs) have shown unstoppable prospects in the field of bionic electronics with their outstanding optoelectronic properties and unique biocompatible characteristics. In this study, a novel CQD-based memristor is proposed for neuromorphic computing. Unlike the models that rely on the formation and rupturing of conductive filaments, it is speculated that the resistance switching mechanism of CQD-based memristors is due to the conductive path caused by the hybridization state transition of the sp2 carbon domain and sp3 carbon domain induced by the reversible electric field. This avoids the drawback of uncontrollable nucleation sites leading to the random formation of conductive filaments in resistive switching. Importantly, it illustrates that the coefficient of variation (CV) of the threshold voltage can be as low as -1.551% and 0.083%, which confirms the remarkable uniform switching characteristics. Interestingly, the Pavlov's dog reflection as an important biological behavior can be demonstrated by the samples. Finally, the accuracy recognition rate of MNIST handwriting can reach up to 96.7%, which is very close to the ideal number (97.8%). A carbon-based memristor based on a new mechanism presented provides new possibilities for the improvement of brain-like computing.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.