High-Speed and Low-Energy\nResistive Switching with\nTwo-Dimensional Cobalt Phosphorus Trisulfide for Efficient Neuromorphic\nComputing

Two-dimensional (2D) materials hold significant potential\nfor the\ndevelopment of neuromorphic computing architectures owing to their\nexceptional electrical tunability, mechanical flexibility, and compatibility\nwith heterointegration. However, the practical implementation of 2D\nmemristors in neuromorphic computing is often hindered by the challenges\nof simultaneously achieving low latency and low energy consumption.\nHere, we demonstrate memristors based on 2D cobalt phosphorus trisulfide\n(CoPS<sub>3</sub>), which achieve impressive performance metrics including\nhigh switching speed (20 ns), low switching energy (1.15 pJ), high\nswitching ratio (>400), and low switching voltages (1.05 V for\nset\nand −0.89 V for reset). The creation of sulfur vacancies in\nCoPS<sub>3</sub> through an electroforming process facilitates the\nformation of conductive filaments, leading to uniform fast switching\nwith minimal energy requirements. The CoPS<sub>3</sub> memristors\nalso show linear conductance modulation and long-term memory retention,\nenabling high-accuracy modeling of artificial neural networks for\nhandwritten digit recognition and convolutional neural networks for\nimage processing. Furthermore, robust memristive switching is achieved\nin solution-processed large-scale CoPS<sub>3</sub> films, underscoring\ntheir potential for wafer-scale, low-temperature integration. The\ncombination of rapid switching, low energy consumption, extended memory\nretention, high switching ratio, linear conductance update, and scalability\nmanifests the potential of 2D CoPS<sub>3</sub> materials for energy-efficient\nneuromorphic computing circuits.