Quaternary PdPS 0.55 Se 0.45 for SBUV‐to‐SWIR Broadband Photodetection and Tri‐Band In‐Sensor Processing

Post‐fire remote sensing for accurate damage assessment critically relies on multi‐band perception spanning from solar‐blind ultraviolet (SBUV) to short‐wave infrared (SWIR) and effective in‐sensor image pre‐processing. However, most vdW photodetectors still operate over limited spectral response, which constrains unified ultraviolet‐visible‐infrared sensing and computing within a single device platform. Here, we develop a stable quaternary vdW semiconductor, PdPS 0.55 Se 0.45 , and demonstrate a single photodetector enabling broadband sensing from SBUV (266 nm) to SWIR (1550 nm) while supporting in‐sensor convolutional processing for remote‐sensing images. The device achieves a peak responsivity ( R ) of 98.13 (84.81) A W −1 and a specific detectivity ( D *) exceeding 10 13 Jones at 266 nm (638 nm). We further exploit the intrinsic power‐density‐dependent responsivity to program band‐specific convolution kernels, where responsivity differences under 266, 638, and 1550 nm illumination are mapped into analog multiply‐accumulate weights. Coupled with a convolutional neural network (CNN), this tri‐band in‐sensor pre‐processing enables robust post‐fire target recognition on noise‐corrupted remote sensing images, achieving a recognition accuracy of ∼96% for post‐fire scenes. This work offers a practical route to SBUV‐to‐SWIR photodetector for in‐sensor computing, advancing broadband perception‐computation integration and creating new opportunities for remote sensing vision under complex environments.