New-Style Logic Operation and Neuromorphic Computing Enabled by Optoelectronic Artificial Synapses in an MXene/Y:HfO<sub>2</sub> Ferroelectric Memristor
Junlin Fang, Zhenhua Tang, Xi-Cai Lai, Fan Qiu, Yanping Jiang, Qiu‐Xiang Liu, Xin‐Gui Tang, Qijun Sun, Yichun Zhou, Jingmin Fan, Ju Gao
Abstract
Today’s computing systems, to meet the enormous demands of information processing, have driven the development of brain-inspired neuromorphic systems. However, there are relatively few optoelectronic devices in most brain-inspired neuromorphic systems that can simultaneously regulate the conductivity through both optical and electrical signals. In this work, the Au/MXene/Y:HfO 2 /FTO ferroelectric memristor as an optoelectronic artificial synaptic device exhibited both digital and analog resistance switching (RS) behaviors under different voltages with a good switching ratio (>10 3 ). Under optoelectronic conditions, optimal weight update parameters and an enhanced algorithm achieved 97.1% recognition accuracy in convolutional neural networks. A new logic gate circuit specifically designed for optoelectronic inputs was established. Furthermore, the device integrates the impact of relative humidity to develop an innovative three-person voting mechanism with a veto power. These results provide a feasible approach for integrating optoelectronic artificial synapses with logic-based computing devices.