Carbon Nanodots Memristor: An Emerging Candidate toward Artificial Biosynapse and Human Sensory Perception System.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Published Date:

Abstract

In the era of big data and artificial intelligence (AI), advanced data storage and processing technologies are in urgent demand. The innovative neuromorphic algorithm and hardware based on memristor devices hold a promise to break the von Neumann bottleneck. In recent years, carbon nanodots (CDs) have emerged as a new class of nano-carbon materials, which have attracted widespread attention in the applications of chemical sensors, bioimaging, and memristors. The focus of this review is to summarize the main advances of CDs-based memristors, and their state-of-the-art applications in artificial synapses, neuromorphic computing, and human sensory perception systems. The first step is to systematically introduce the synthetic methods of CDs and their derivatives, providing instructive guidance to prepare high-quality CDs with desired properties. Then, the structure-property relationship and resistive switching mechanism of CDs-based memristors are discussed in depth. The current challenges and prospects of memristor-based artificial synapses and neuromorphic computing are also presented. Moreover, this review outlines some promising application scenarios of CDs-based memristors, including neuromorphic sensors and vision, low-energy quantum computation, and human-machine collaboration.

Authors

  • Cheng Zhang
    College of Forestry, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China.
  • Mohan Chen
    National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China.
  • Yelong Pan
    Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application, School of Physical Science and Technology, Suzhou University of Science and Technology, Suzhou, Jiangsu, 215009, China.
  • Yang Li
    Occupation of Chinese Center for Disease Control and Prevention, Beijing, China.
  • Kuaibing Wang
    Jiangsu Key Laboratory of Pesticide Sciences, Department of Chemistry, College of Science, Nanjing Agricultural University, Nanjing, 210095, China.
  • Junwei Yuan
    School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou, Jiangsu, 215009, China.
  • Yanqiu Sun
    School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou, Jiangsu, 215009, China.
  • Qichun Zhang
    Department of Computer Science, University of Bradford, Bradford BD7 1DP, UK.