Biorealistic Neuronal Temperature-Sensitive Dynamics within Threshold Switching Memristors: Toward Neuromorphic Thermosensation.

Neuromorphic nanoelectronic devices that can emulate the temperature-sensitive dynamics of biological neurons are of great interest for bioinspired robotics and advanced applications such as in silico neuroscience. In this work, we demonstrate the biomimetic thermosensitive properties of two-terminal V3O5 memristive devices and showcase their similarity to the firing characteristics of thermosensitive biological neurons. The temperature-dependent electrical characteristics of V3O5-based memristors are used to understand the spiking response of a simple relaxation oscillator. The temperature-dependent dynamics of these oscillators are then compared with those of biological neurons through numerical simulations of a conductance-based neuron model, the Morris-Lecar neuron model. Finally, we demonstrate a robust neuromorphic thermosensation system inspired by biological thermoreceptors for bioinspired thermal perception and representation. These results not only demonstrate the biorealistic emulative potential of threshold-switching memristors but also establish V3O5 as a functional material for realizing solid-state neurons for neuromorphic computing and sensing applications.

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 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.

Physical Origin of Negative Differential Resistance in V3 O5 and Its Application as a Solid-State Oscillator.

Oxides that exhibit an insulator-metal transition can be used to fabricate energy-efficient relaxation oscillators for use in hardware-based neural networks but there are very few oxides with transition temperatures above room temperature. Here the structural, electrical, and thermal properties of V3 O5 thin films and their application as the functional oxide in metal/oxide/metal relaxation oscillators are reported. The V3 O5 devices show electroforming-free volatile threshold switching and negative differential resistance (NDR) with stable (<3% variation) cycle-to-cycle operation. The physical mechanisms underpinning these characteristics are investigated using a combination of electrical measurements, in situ thermal imaging, and device modeling. This shows that conduction is confined to a narrow filamentary path due to self-confinement of the current distribution and that the NDR response is initiated at temperatures well below the insulator-metal transition temperature where it is dominated by the temperature-dependent conductivity of the insulating phase. Finally, the dynamics of individual and coupled V3 O5 -based relaxation oscillators is reported, showing that capacitively coupled devices exhibit rich non-linear dynamics, including frequency and phase synchronization. These results establish V3 O5 as a new functional material for volatile threshold switching and advance the development of robust solid-state neurons for neuromorphic computing.