Abstract
Silicon-based photodetectors operating in the near-infrared (NIR) wavelength range (λ = 700-1,100 nm) are essential for applications such as light detection and ranging, facial recognition, and eye-tracking. However, silicon's low absorption coefficient in this range limits photodetection efficiency. While recent advances in nano-diffraction structures have improved photo-absorption by increasing the effective absorption path, optimizing carrier dynamics remains challenging. In the NIR regime, photons penetrate deeply into the silicon substrate, making it critical to align the spatial distribution of photo-generated carriers with the charge collection regions. However, the angular and spatial behavior of carrier generation (CG) and collection under nano-diffraction structures remain underexplored. This study presents an analytical model that visualizes CG pathways and corresponding collection probabilities induced by plasmonic diffraction structures, providing insight into diffraction-driven CG in silicon. The model is experimentally validated through photocurrent responses in non-illuminated neighboring pixels, directly revealing plasmonic diffraction effects. The results show that diffraction enhances light absorption and enables visualization of the CG and collection pathways based on the diffraction angle. This approach enables the spatial overlap of CG and collection pathways, efficiently guiding incident photons to photosensitive regions. This framework offers a new strategy to enhance NIR photodetector performance through diffraction-guided light propagation and device-specific modeling.