Experiment and Simulation in Silicon PN-Junction Photodetectors: Insights into Electrical and Optical Transport

Silicon PN junctions remain central to optoelectronic technologies due to their maturity and CMOS compatibility. We report the fabrication and comprehensive optoelectronic characterization of a silicon PN-junction photodiode demonstrating stable operation over a wide temperature range. The device exhibits excellent diode behavior, with a rectification ratio exceeding four orders of magnitude, an ideality factor close to unity above 0.3 V, and a series resistance below 100 Ω. Under white-light illumination, the photodiode shows a linear photocurrent response over broad optical power and temperature ranges, achieving an average responsivity of 0.3 A·W-1. We implement a machine learning framework based on an Artificial Neural Network to perform global parameter estimation, demonstrating its effectiveness in generalizing across diverse experimental datasets. Moreover, we propose a comprehensive analytical model, validated by Atlas–Silvaco simulations, that successfully captures charge transport and photogeneration mechanisms. This integrated approach, combining experimental measurements, machine learning, numerical simulations and analytical modelling, provides a robust performance benchmark and deeper insights for optimizing silicon-based optoelectronic devices.