ZTO/MgO-Based Optoelectronic Synaptic Memristor for Neuromorphic Computing

Chia Cheng Hsu, Saransh Shrivastava, Sparsh Pratik, Sridhar Chandrasekaran, Tseung Yuen Tseng

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Synapse having good linearity plays a vital role in the memory and computing of human brain. Therefore, the achievement of efficient learning process in neuromorphic computing by the implementation of the synaptic functions, such as long-term potentiation/ depression (LTP/LTD) and spike time-dependent plasticity (STDP) of two-terminal optoelectronic memristor device, is critical for the next-generation artificial intelligence. In this work, we improve the resistive switching and synaptic characteristics of a Zn<inline-formula> <tex-math notation="LaTeX">$_{\text{2}}$</tex-math> </inline-formula>SnO<inline-formula> <tex-math notation="LaTeX">$_{\text{4}}$</tex-math> </inline-formula> (ZTO)-based optoelectronic synaptic memristor (OSM) by the insertion of an ultrathin MgO layer. For this bilayer (BL) structured OSM, the nonlinearities of LTP and LTD curves are improved to 1.96 and 0.33, respectively. Asymmetrical STDP response demonstrates the suitability of device toward the Hebbian learning. In addition, a Hopfield neural network (HNN) is successfully trained to recognize a 10 <inline-formula> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> 10 pixel input image with an accuracy of <inline-formula> <tex-math notation="LaTeX">$\sim$</tex-math> </inline-formula>100% after 15 iterations. Under blue light (405 nm) illumination, OSM emulates the synaptic functions, such as paired pulse facilitation, learning experience behavior, and short-to long-term memory transition. The photoresponse and relaxation characteristics of the device depend on the ionization and neutralization of oxygen vacancies. This highly transparent ZTO/MgO-based OSM with the convergence of &#x201C;nonvolatile electronic memory and visible light sensor&#x201D; is suitable as an artificial synapse for neuromorphic computing applications.

Original languageEnglish
Pages (from-to)1-7
Number of pages7
JournalIEEE Transactions on Electron Devices
DOIs
StateAccepted/In press - 2023

Keywords

  • Artificial synapse
  • Behavioral sciences
  • Hopfield neural network (HNN)
  • Memristors
  • neuromorphic computing
  • Optical device fabrication
  • Optical imaging
  • Optical switches
  • optoelectronic synaptic memristor (OSM)
  • Performance evaluation
  • Synapses

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