Enhancing High-Speed Artificial Neuron Functionality via Vanadium Oxide Resistive Switching on Perovskite Substrates

This study confronts the urgent challenge of rising energy consumption in the realm of information technology and the constraints imposed on conventional computing by issues like the Memory wall, Heat wall, and Moore's law. In response to this, there is a growing demand for a novel, energy-efficient computing paradigm inspired by the human brain, known as neuromorphic computing. These neuromorphic systems are composed of artificial synapses and neurons, with the intention of replicating the brain's nonlinear operations and its capacity for in-memory computing. Although progress has been made in creating memristive devices to mimic adaptable synaptic weights, the development of artificial neuron devices is still in its nascent stages. The use of vanadium oxide-based resistive switching is particularly promising due to its unique attributes, such as reversible phase transitions and impressive electrical conductivity, positioning it as a candidate for the development of energy-efficient, brain-inspired computing systems. This research centers on the exploration of VOx thin films grown on La_0.7Sr_0.3MnO₃-buffered (111) perovskite substrates, with the aim of achieving low-energy consumption, a crucial advancement in the field of neuromorphic computing.