Ferroelectric Modulation of ReS₂‐Based Multifunctional Optoelectronic Neuromorphic Devices for Wavelength‐Selective Artificial Visual System

Abstract Neuromorphic optoelectronic vision system inspired by the biological platform displays potential for in‐sensor computing. However, it is still challenge to process multiwavelength image in noisy environment with simple device configuration and light‐tunable biological plasticity. Here, a prototype visual sensor is demonstrated based on ferroelectric copolymer poly(vinylidene fluoride‐trifluoroethylene) (P(VDF‐TrFE)) and 2D rhenium disulfide (ReS₂) with integration of recognition, memorization, and pre‐processing functions in the same device. Such synaptic devices achieve impressive electronic characteristics, including a current on/off ratio of 10⁹ and mobility of 45 cm² V⁻¹ s⁻¹. Various synaptic plasticity behaviors have been achieved owing to the switchable ferroelectricity, enabling them to establish an artificial neural network (ANN) with high digit recognition accuracy of 89%. Through constructing optoelectronic device array, object extraction is achieved with wavelength‐selective capability in noisy environment, closely resembling human retina for color recognition. Above outcomes bring a notable improvement in the image recognition rate from 72% to 96%. Besides, low energy consumption comparable to single biological event can be realized. With these multifunctional features, this work inspires highly integrated neuromorphic systems and the development of wavelength‐selective artificial visual platform.