Extreme Illuminated Vision Processing with a Graded Alloyed Perovskite In-sensor Computing Network

In-sensor computing is proposed to reduce energy expenditure and processing latency by unifying sensing and computation within the hardware layer, yet the application under extreme illuminating scenario remains constrained by simultaneously obtaining broadband responsivity, large linear dynamic range and fast response. Here, we report a fully vapor-deposited graded Pb-Sn alloyed perovskite heterojunction photodiode with improved crystal quality. It enables the detection of light from visible to infrared light with a 230 dB linear dynamic range and 33 ns response time. We also develop a wafer-scale imaging processor by integrating the photodiode to a reconfigurable array. With this approach, we demonstrate biomedical detection and spatiotemporal trajectory encoding. The in-sensor processor realizes low-power high-resolution visible to infrared wavelength edge detection, adaptive background suppression under dim light and noise-immune high-speed dynamic imaging. Our results extend the options for in-sensor computing hardware, and thus pave a way toward practical artificial intelligent machine vision. Zhan et al. report a fully vapor-deposited graded perovskite photodiode for visible-to-IR imaging with 230 dB linear dynamic range and 33 ns response time. Wafer-scale reconfigurable imaging processor is developed for edge detection, adaptive background suppression under dim light, and noise-immune high-speed dynamic imaging.