Single-Molecule Memristor Realizing Synaptic Plasticity for Neuromorphic Applications

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.