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Memristive Switching Mechanism in Colloidal InP/ZnSe/ZnS Quantum Dot-Based Synaptic Devices for Neuromorphic Computing.

Geun Woo BaekYeon Jun KimJaekwon KimJun Hyuk ChangUhjin KimSoobin AnJunhyeong ParkSunkyu YuWan Ki BaeJaehoon LimSoo-Yeon LeeJeonghun Kwak
Published in: Nano letters (2024)
Quantum dots (QDs) have garnered a significant amount of attention as promising memristive materials owing to their size-dependent tunable bandgap, structural stability, and high level of applicability for neuromorphic computing. Despite these advantageous properties, the development of QD-based memristors has been hindered by challenges in understanding and adjusting the resistive switching (RS) behavior of QDs. Herein, we propose three types of InP/ZnSe/ZnS QD-based memristors to elucidate the RS mechanism, employing a thin poly(methyl methacrylate) layer. This approach not only allows us to identify which carriers (electron or hole) are trapped within the QD layer but also successfully demonstrates QD-based synaptic devices. Furthermore, to utilize the QD memristor as a synapse, long-term potentiation/depression (LTP/LTD) characteristics are measured, resulting in a low nonlinearity of LTP/LTD at 0.1/1. On the basis of the LTP/LTD characteristics, single-layer perceptron simulations were performed using the Extended Modified National Institute of Standards and Technology, verifying a maximum recognition rate of 91.46%.
Keyphrases
  • quantum dots
  • sensitive detection
  • energy transfer
  • depressive symptoms
  • molecular dynamics
  • prefrontal cortex
  • quality improvement
  • electron transfer