RT Journal Article
T1 Experiment and simulation in silicon PN-junction photodetectors: insights into electrical and optical transport
A1 Khaouani, Mohammed
A1 Sessa, Andrea
A1 De Stefano, Sebastiano
A1 Rouigueb, Hichem
A1 Belbachir, Mohammed Anes
A1 Mazzotti, Adolfo
A1 Pelella, Aniello
A1 Durante, Ofelia
A1 Di Bartolomeo, Antonio
A1 García Hemme, Eric
AB 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.
PB Elsevier
SN 0921-4526
YR 2026
FD 2026-05
LK https://hdl.handle.net/20.500.14352/136750
UL https://hdl.handle.net/20.500.14352/136750
LA eng
NO Khaouani, Mohammed, et al. «Experiment and Simulation in Silicon PN-Junction Photodetectors: Insights into Electrical and Optical Transport». Physica B: Condensed Matter, vol. 730, mayo de 2026, p. 418479. DOI.org (Crossref), https://doi.org/10.1016/j.physb.2026.418479.
NO © 2026 The Authors.
NO Université de Salerne
NO Ministerio de Ciencia e Innovación (España)
NO European Commission
NO Agencia Estatal de Investigación (España)
NO Comunidad de Madrid
DS Docta Complutense
RD 8 jun 2026