Artificial nociceptor based on TiO2 nanosheet memristor

Abstract

With the development of technology, the learning and memory functions of artificial memristor synapses are necessary for realizing artificial neural networks and neural neuromorphic computing. Owing to their high scalability performance, nanosheet materials have been widely employed in cellular-level learning, but the behaviors of nociceptor based on nanosheet materials have rarely been studied. Here, we present a memristor with an Al/TiO2/Pt structure. After electroforming, the memristor device showed a gradual conductance regulation and could simulate synaptic functions such as the potentiation and depression of synaptic weights. We also designed a new scheme that verifies the pain sensitization, desensitization, allodynia, and hyperalgesia behaviors of real nociceptors in the fabricated memristor. Memristors with these behaviors can significantly improve the quality of intelligent electronic devices. Data fitting showed that the high resistance and low resistance states were consistent with the hopping conduction mechanism. This work promises the application of TiO2-based devices in next-generation neuromorphological systems.