Efficient Resistive Switching and Spike Rate Dependent Plasticity in a New CuCrO2 Memristor for Plausible Neuromorphic Systems - Caffrey, David; Shvets, Igor (My University, 2020)
In this work, we introduce a new class of p-type transparent conductive oxide (TCO) CuCrO2 (150 nm) heterogeneously integrated onto FTO/glass for forming free memristor based neuromorphic applications. The fabricated Al/CuCrO2/FTO memristors demonstrate a reliable bipolar resistive switching with an ON/OFF ratio of 1000. The retention of the device was found to be steady even beyond 106 s, which demonstrates its non-volatility. The current-voltage (I-V) characteristics were fitted to evaluate its transport properties and a band-diagram was projected to have a better insight of the device operational principles. To validate the experimental observations, a new model has been developed, and the simulated I-V behavior was analogues to the experimental one. Efforts were then devoted to observe long-term potentiation (LTP) and longterm depression (LTD) utilizing identical but opposite pulses to evaluate the device’s efficacy for synaptic applications. The synaptic behavior was well controlled by the pulse (pulse amplitude and width) variations. The conductance change was found to be symmetric and then saturated, which reflects the popular biological Hebbian rules. Finally, a long-term synaptic modulation has been implemented by establishing the spike rate dependent plasticity (SRDP) rule, which is a part of spiking neural networks and advantageous to mimic the brain’s capability at low power. All the obtained experimental results were systematically corroborated by neural network simulation. Overall, our approach provides a new road map towards the development of TCO based alternative memristors, which can be employed to mimic the synaptic plasticity for energy-efficient bioinspired neuromorphic systems and non-Von Neumann computer architectures.
PUBLISHED
Keywords: Materials science; CuCrO; Memristor