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. • A silicon PN-junction photodiode was fabricated and thoroughly characterized, exhibiting excellent rectification (>10 4 ), low series resistance (<100 Ω), and near-ideal diode behavior. • Multiple charge-transport mechanisms were identified and modeled, with the full I–V characteristics accurately described using a double-diode phenomenological model. • The device shows highly linear photocurrent response over wide ranges of optical power and temperature, with a stable wavelength-averaged responsivity of ∼0.3 A W -1 under white-light illumination. • Temperature-dependent measurements reveal thermally activated leakage currents, with an activation energy close to half the silicon bandgap, limiting detectivity at elevated temperatures. • Excellent agreement between experiment, analytical theory, and Atlas–Silvaco simulations validates the proposed modeling framework and provides reliable insight into silicon PN photodiode physics.

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Publication Details

Journal
Physica B Condensed Matter
Published
2026-03-05
DOI
https://doi.org/10.1016/j.physb.2026.418479
Primary Topic
Advancements in Semiconductor Devices and Circuit Design
Type
article
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article

Experiment and simulation in silicon PN-junction photodetectors: Insights into electrical and optical transport

Aniello Pelella, S. De Stefano, O. Durante, E. García-Hemme et al.
Physica B Condensed Matter
Advancements in Semiconductor Devices and Circuit Design
article

Experiment and simulation in silicon PN-junction photodetectors: Insights into electrical and optical transport

Aniello Pelella, S. De Stefano, O. Durante, E. García-Hemme, Andrea Sessa, M. Khaouani, Antonio Di Bartolomeo, Adolfo Mazzotti, Hichem Rouigueb, Mohammed Anes Belbachir
article en

Abstract

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. • A silicon PN-junction photodiode was fabricated and thoroughly characterized, exhibiting excellent rectification (>10 4 ), low series resistance (<100 Ω), and near-ideal diode behavior. • Multiple charge-transport mechanisms were identified and modeled, with the full I–V characteristics accurately described using a double-diode phenomenological model. • The device shows highly linear photocurrent response over wide ranges of optical power and temperature, with a stable wavelength-averaged responsivity of ∼0.3 A W -1 under white-light illumination. • Temperature-dependent measurements reveal thermally activated leakage currents, with an activation energy close to half the silicon bandgap, limiting detectivity at elevated temperatures. • Excellent agreement between experiment, analytical theory, and Atlas–Silvaco simulations validates the proposed modeling framework and provides reliable insight into silicon PN photodiode physics.

Physica B Condensed MatterVol. 730
Universidad Complutense de Madrid (ES), University of Salerno (IT), University of Abou Bekr Belkaïd (DZ), Université de ain Témouchent (DZ)
Openalex Percentile: Top 34%
Advancements in Semiconductor Devices and Circuit Design
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