Fully Photon Controlled Synaptic Memristor for Neuro-Inspired Computing

Saransh Shrivastava, Lai Boon Keong, Sparsh Pratik, Albert S. Lin, Tseung Yuen Tseng*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The emerging optoelectronic memristive synapses having the advantages of both optics and electronics exhibit a great potential in neuro-inspired computing, which is a new generation of artificial intelligence. Herein, a light stimulated synaptic memristor (LSSM) based on ZnO/Zn2SnO4 heterostructure is prepared with the characteristics of reversibly tunable conductance states by varying the wavelength of the incident light. The synaptic feature of this fully photon controlled memristive synapse is revealed by potentiation and depression behaviors stimulated by violet and red light pulses, respectively. Similar to biological brain, the device demonstrates the dynamic learning and forgetting behavior. All-optically driven and bio-vision inspired image processing function such as contrast enhancement is exemplified. The international Morse code for Arabic numerals (0–9) is also successfully conveyed by patterned light pulses and suggests the device's potential in the field of optical wireless communication for human–machine interface. Classical Pavlovian conditioning (associative learning) is successfully demonstrated through visible light induction. Finally, the device can realize the recognition application of Zalando's article image through the simulation based on Hopfield neural network (HNN). This work provides a promising approach toward optoelectronic neural systems and human–machine interaction technologies.

Original languageEnglish
JournalAdvanced Electronic Materials
DOIs
StateAccepted/In press - 2023

Keywords

  • artificial synapse
  • fully photon controlling
  • long term memory
  • neuro-inspired computing
  • optoelectronic memristor

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