Advanced Electronic Materials (Jul 2023)

Biological UV Photoreceptors‐Inspired Sn‐Doped Polycrystalline β‐Ga2O3 Optoelectronic Synaptic Phototransistor for Neuromorphic Computing

  • Youngbin Yoon,
  • Youngki Kim,
  • Wan Sik Hwang,
  • Myunghun Shin

DOI
https://doi.org/10.1002/aelm.202300098
Journal volume & issue
Vol. 9, no. 7
pp. n/a – n/a

Abstract

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Abstract In this study, the authors fabricate Sn‐doped 100‐nm thick polycrystalline β‐Ga2O3 synaptic field‐effect transistors (FETs) emulating optical and electrical spike stimulation. When stimulated by deep ultraviolet (UV) optical spikes or electric voltage spikes at the gate, the devices exhibit several essential synaptic functions of excitatory‐postsynaptic currents (EPSCs), inhibitory‐postsynaptic currents (IPSCs), paired‐pulse facilitation (PPF), spike‐number‐dependent plasticity (SNDP), and spike‐timing‐dependent plasticity (STDP). Following UV optical stimulation, the devices mimic synaptic plasticity with a photogate effect, and the gate voltage stimulation emulates the synaptic weights according to the state of the gate dielectric interface. The β‐Ga2O3 synaptic FET demonstrates synergistic functions in various optoelectronic stimulation modes and successfully mimics the visual memory formation in bees with UV photoreceptors. Moreover, to verify the translation of optoelectrical‐derived synaptic behaviors of β‐Ga2O3 synaptic FETs into artificial neuromorphic computing, handwritten digit image recognition of the Modified National Institute of Standards and Technology dataset is performed using a convolutional neural network, and a learning accuracy of 96.92% is achieved. The realization of these fundamental functions of biological synapses suggests the utility of Ga2O3‐based optoelectronic devices for next‐generation neuromorphic computing.

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