Optically Tunable Electrical Oscillations in Oxide‐Based Memristors for Neuromorphic Computing
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 electrofo...
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Veröffentlicht in: | Advanced materials (Weinheim) 2024-06, Vol.36 (25), p.e2400904-n/a |
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Sprache: | eng |
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Zusammenfassung: | 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, V3O5 is identified as a new bolometric material with a temperature coefficient of resistance (TCR) as high as −4.6% K−1 at 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.
This study reports light‐control of an oxide‐based relaxation oscillator based on the photothermal response of V3O5, a material that undergoes an insulator‐to‐metal transition at temperatures above ≈420 K. The research advances the understanding of V3O5 as a functional material, and demonstrates its potential as the basis of a solid‐state sensory neuron for neuromorphic computing. |
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ISSN: | 0935-9648 1521-4095 1521-4095 |
DOI: | 10.1002/adma.202400904 |