Oxygen vacancies modulated VO2 for neurons and Spiking Neural Network construction
CoRR(2024)
摘要
Artificial neuronal devices are the basic building blocks for neuromorphic
computing systems, which have been motivated by realistic brain emulation.
Aiming for these applications, various device concepts have been proposed to
mimic the neuronal dynamics and functions. While till now, the artificial
neuron devices with high efficiency, high stability and low power consumption
are still far from practical application. Due to the special insulator-metal
phase transition, Vanadium Dioxide (VO2) has been considered as an idea
candidate for neuronal device fabrication. However, its intrinsic insulating
state requires the VO2 neuronal device to be driven under large bias voltage,
resulting in high power consumption and low frequency. Thus in the current
study, we have addressed this challenge by preparing oxygen vacancies modulated
VO2 film(VO2-x) and fabricating the VO2-x neuronal devices for Spiking Neural
Networks (SNNs) construction. Results indicate the neuron devices can be
operated under lower voltage with improved processing speed. The proposed VO2-x
based back-propagation SNNs (BP-SNNs) system, trained with the MNIST dataset,
demonstrates excellent accuracy in image recognition. Our study not only
demonstrates the VO2-x based neurons and SNN system for practical application,
but also offers an effective way to optimize the future neuromorphic computing
systems by defect engineering strategy.
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