High-Resolution Multispectral Photovoltaic Imagers from Visible to Short-Wave Infrared.

Visible to short-wave infrared multispectral imaging is gaining significant attention across various fields, including agriculture, security, and medical diagnostics. Traditional multispectral imaging systems often rely on separate sensors for different spectral bands, leading to complex optical alignment and irreversible resolution loss. Here, we present hardware-algorithm co-designed architecture to achieve multispectral super-resolution imaging. Specifically, we demonstrate a monolithic quad-spectral photovoltaic imaging platform featuring a resolution of 640 × 512 pixels with <1% dead pixels per channel. The system achieves broadband spectral integration from visible to short-wave infrared (350-2350 nm) by combining an all-polymer bulk heterojunction with colloidal quantum dots within a single CMOS-compatible architecture. The compatibility of all-polymer bulk heterojunction with direct photopatterning allows for precise patterning and high-density integration, enabling the devices to operate efficiently in photovoltage mode. To address resolution degradation inherent in planar-integrated spectral sensing architectures, we applied a super-resolution reconstruction method, restoring images to a resolution of 640 × 512. The demonstrated capability to simultaneously capture and process multispectral data paves the way for CMOS integration, multispectral Imagers, organic photodetector, super-resolution reconstruction applications in diverse fields, from precision agriculture to medical diagnostics and beyond.