Reconfigurable, non-volatile neuromorphic photovoltaics

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. A neuromorphic photovoltaic detector with highly tunable responsivity and simultaneous non-volatile storage of image data has been demonstrated in a neural network, representing a transformative leap in the compactness and function of visual perception hardware.