The neural network image sensor—which mimics neurobiological functions of the human retina—has recently been demonstrated to simultaneously sense and process optical images. However, highly tunable responsivity concurrent with non-volatile storage of image data in the neural network would allow a transformative leap in compactness and function of these artificial neural networks. Here, we demonstrate a reconfigurable and non-volatile neuromorphic device based on two-dimensional semiconducting metal sulfides that is concurrently a photovoltaic detector. The device is based on a metal–semiconductor–metal (MSM) two-terminal structure with pulse-tunable sulfur vacancies at the M–S junctions. By modulating sulfur vacancy concentrations, the polarities of short-circuit photocurrent can be changed with multiple stable magnitudes. The bias-induced motion of sulfur vacancies leads to highly reconfigurable responsivities by dynamically modulating the Schottky barriers. A convolutional neuromorphic network is finally designed for image processing and object detection using the same device. The results demonstrated that neuromorphic photodetectors can be the key components of visual perception hardware.

神经网络图像传感器模仿人类视网膜的神经生物学功能，最近被证明可以同时感知和处理光学图像。然而，高度可调的响应度与神经网络中图像数据的非易失性存储相结合，将使这些人工神经网络的紧凑性和功能发生革命性的飞跃。在这里，我们展示了一种基于二维半导体金属硫化物的可重构且非易失性神经形态装置，同时也是一个光伏探测器。该器件基于金属-半导体-金属 (MSM) 两端结构，M-S 结处具有脉冲可调硫空位。通过调节硫空位浓度，可以以多个稳定的幅度改变短路光电流的极性。偏置引起的硫空位运动通过动态调节肖特基势垒导致高度可重构的响应度。最终设计了一个卷积神经形态网络，使用同一设备进行图像处理和目标检测。结果表明，神经形态光电探测器可以成为视觉感知硬件的关键组件。