Single‐Molecule Memristor Realizing Synaptic Plasticity for Neuromorphic Applications
Li‐Yu‐Yang Shi, Yun‐Tao Ding, Xiao‐Di Liu, Shun‐Da Wu, Wen‐Jing Sun, Bing Sun, Yi‐Sheng Wei, Zheng Zhang, Shu‐Tong Liu, Lichuan Chen, Dong Xiang, Yamin Zhang, Zitong Liu, Hao‐Li ZhangABSTRACT
Neuromorphic computing, particularly memristor‐based architectures, offers a promising route to overcome the von Neumann bottleneck. Single‐molecule devices, with their high integration density and low energy consumption, represent an emerging platform for next‐generation computing. Here, we report the first optoelectronic volatile single‐molecule memristor based on the organic photovoltaic material Y6. The device exhibits reproducible conductance switching driven by electric‐field‐induced structural relaxation, enabling gradual and linear conductance modulation that mimics synaptic behavior. Under red‐light illumination, the Y6 junction shows a remarkable 457% increase in conductance and a significantly reduced switching threshold, demonstrating strong photoresponsivity and low‐power operation. Furthermore, frequency‐dependent pulse tests clearly reproduce short‐term synaptic plasticity (STP), demonstrating the memristor's ability to emulate dynamic synaptic functions. When the experimentally measured current response of the Y6 single‐molecule memristor is incorporated into an artificial neural network (ANN) model, the system achieves a speech‐recognition accuracy of 71.50%, closely matching that of the benchmark ANN (74.90%). This work pioneers the realization of synaptic functionality in a single‐molecule memristor and validates its application within an artificial neural network. It provides a new strategy for developing highly integrated molecular‐scale neuromorphic computing devices.