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Title: Optically Tunable Electrical Oscillations in Oxide‐Based Memristors for Neuromorphic Computing
Abstract The application of hardware‐based neural networks can be enhanced by integrating sensory neurons and synapses that enable direct input from external stimuli. This work reports direct optical control of an oscillatory neuron based on volatile threshold switching in V3O5. The devices exhibit electroforming‐free operation with switching parameters that can be tuned by optical illumination. Using temperature‐dependent electrical measurements, conductive atomic force microscopy (C‐AFM), in situ thermal imaging, and lumped element modelling, it is shown that the changes in switching parameters, including threshold and hold voltages, arise from overall conductivity increase of the oxide film due to the contribution of both photoconductive and bolometric characteristics of V3O5, which eventually affects the oscillation dynamics. Furthermore, V3O5is identified as a new bolometric material with a temperature coefficient of resistance (TCR) as high as −4.6% K−1at 423 K. The utility of these devices is illustrated by demonstrating in‐sensor reservoir computing with reduced computational effort and an optical encoding layer for spiking neural network (SNN), respectively, using a simulated array of devices.  more » « less
Award ID(s):
2033328
PAR ID:
10510360
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more » ; ; « less
Publisher / Repository:
Wiley
Date Published:
Journal Name:
Advanced Materials
ISSN:
0935-9648
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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