Event-Driven CsPbBr3 Perovskite Visual Neurons for Motion Direction Recognition in Low-Light Scenes

The event-driven visual neuron system can enhance the efficiency of visual data processing at sensor terminals, due to its capability for sensing and encoding information with event-driven characteristics for neuromorphic computing. Here, we demonstrate an event-driven CsPbBr3 perovskite visual neuron system consisting solely of a single CsPbBr3 perovskite photodiode and simple circuit overhead. Compared with conventional event-based cameras with Si photodiode, this system enables energy-efficient event-driven light intensity encoding with a greatly simplified sensor circuit design. Our visual neurons utilize self-powered CsPbBr3 perovskite photodiode, which inherently features a high dynamic range of 160 dB. The CsPbBr3 visual neurons can detect dynamic changes in dim visual scenes with the light intensity as low as $0.89~\mu $ W/cm2. Besides, they achieve the fastest event respond with a temporal resolution of $1.4~\mu $ s. Finally, CsPbBr3 perovskite visual neurons are incorporated as input neurons in a simulated three-layer spiking neural network (SNN), achieving 99% accuracy in motion direction recognition tasks.