Voltage‐Modulated MoS ₂ /Au Two‐Terminal Optoelectronic Synapses for Wavelength‐Selective Neuromorphic Computing

Two‐terminal optoelectronic synapses have garnered great attention in neuromorphic computing due to their advantages in structural simplicity and energy efficiency. However, the device's operational flexibility is fundamentally limited by its spectral and electrical characteristics, which fail to tune photoresponses with wavelength selectivity and voltage modulation. Here, a MoS 2 /Au nanoparticle two‐terminal optoelectronic synapse is presented that simultaneously achieves wavelength selectivity and voltage‐modulated memory control. Adjusting the morphology of Au nanoparticles enables selective maximum photoresponses across the green and red wavelength regions, and voltage modulation induces switching between short‐term and long‐term memory states, thereby enhancing functional versatility. Based on this tunable photoresponse of the synapse, wavelength‐selective image denoising and recognition tasks are demonstrated, achieving a maximum classification accuracy of 98.03% at 520 nm across the visible wavelength range. A wavelength‐selective and voltage‐modulated task for road condition classification is also implemented, incorporating an artificial neural network to track color‐coded vehicles and classify their movement trajectories with precise directional recognition (96.67% accuracy). This work demonstrates a highly tunable optoelectronic synapse that achieves concurrent wavelength selectivity and voltage modulation in a single device, enabling neuromorphic computing and providing a practical strategy for developing highly efficient, multifunctional neuromorphic architectures.