Subthreshold and reverse bias model of graphene/p-type silicon Schottky diodes

This work presents a novel approach to studying, simulating, and modeling the graphene-silicon interface in Schottky diodes by integrating quantum-mechanical and device-level analyses. Such devices hold great performance potential in photodetecting, energy-harvesting, and sensing applications. Quantum-mechanical calculations determine key structural and electronic properties, such as the work function and effective mass, which are critical for understanding the interface’s behavior. These parameters are then incorporated into finite-element simulations, solving the Poisson and Continuity equations to develop a subthreshold and reverse bias model for the graphene/p-type silicon Schottky device. The model characterizes J-V curves, identifying dominant electron transport mechanisms like thermionic emission and diffusion at varying recombination velocities. It also sheds light on the image-force lowering effect, which significantly impacts current density, especially under reverse bias conditions, by modulating the Schottky barrier height. The model is validated by comparing the model with experimental data from graphene-silicon photodetectors, demonstrating its accuracy in predicting device performance. This approach offers valuable insights into optimizing any kind of Schottky diodes. By effectively bridging quantum-mechanical theory with practical device performance, the model proves to be a powerful tool for designing advanced semiconductor devices with enhanced efficiency and functionality, ensuring consistency from the atomistic to the device level.

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Publication Details

Journal
Journal of Science Advanced Materials and Devices
Published
2025-06-19
DOI
https://doi.org/10.1016/j.jsamd.2025.100925
Citations
1
Primary Topic
Graphene research and applications
Type
article
Field-Weighted Citation Impact
0.52
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article

Subthreshold and reverse bias model of graphene/p-type silicon Schottky diodes

J.I. Paredes, Luis Miguel Prócel, Katty Beltrán, A. Hurtado Sanchez et al.
1 citations
Journal of Science Advanced Materials and Devices
Graphene research and applications
0.52
article

Subthreshold and reverse bias model of graphene/p-type silicon Schottky diodes

J.I. Paredes, Luis Miguel Prócel, Katty Beltrán, A. Hurtado Sanchez, Paul Prócel, F. Javier Torres, Olindo Isabella, Maurizio Casalino, César Zambrano
article en
1 citations

Abstract

This work presents a novel approach to studying, simulating, and modeling the graphene-silicon interface in Schottky diodes by integrating quantum-mechanical and device-level analyses. Such devices hold great performance potential in photodetecting, energy-harvesting, and sensing applications. Quantum-mechanical calculations determine key structural and electronic properties, such as the work function and effective mass, which are critical for understanding the interface’s behavior. These parameters are then incorporated into finite-element simulations, solving the Poisson and Continuity equations to develop a subthreshold and reverse bias model for the graphene/p-type silicon Schottky device. The model characterizes J-V curves, identifying dominant electron transport mechanisms like thermionic emission and diffusion at varying recombination velocities. It also sheds light on the image-force lowering effect, which significantly impacts current density, especially under reverse bias conditions, by modulating the Schottky barrier height. The model is validated by comparing the model with experimental data from graphene-silicon photodetectors, demonstrating its accuracy in predicting device performance. This approach offers valuable insights into optimizing any kind of Schottky diodes. By effectively bridging quantum-mechanical theory with practical device performance, the model proves to be a powerful tool for designing advanced semiconductor devices with enhanced efficiency and functionality, ensuring consistency from the atomistic to the device level.

Journal of Science Advanced Materials and DevicesVol. 10(3)
Institut National Polytechnique de Toulouse (FR), Institute of Applied Science and Intelligent Systems (IT), Universidad San Francisco de Quito (EC), University of Delaware (US), Delft University of Technology (NL)
Affordable and clean energy
Openalex Percentile: Top 37%
Graphene research and applications
0.52
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