SimulH: A Semiclassical Monte Carlo Framework for Transport Modeling in Monolayer Graphene Field-Effect Transistors

We present SimulH, a semiclassical Monte Carlo framework developed to model carrier transport in monolayer graphene field-effect transistors (GFETs), where achieving both physical accuracy and computational efficiency remains a key challenge for high-frequency device applications. The model is based on the Boltzmann transport equation and incorporates stochastic Monte Carlo simulations to describe carrier dynamics, including electron–phonon, electron–impurity, and electron–electron scattering processes, as well as quantum capacitance and contact resistance effects. To ensure a consistent description across operating conditions, three complementary approaches are used to evaluate the drain current. The results show strong agreement with reported experimental data, with prediction accuracies above 90% for mobility, capacitance behavior, and charge distribution. Simulations involving more than 40,000 carriers provide detailed insight into transport behavior and scattering mechanisms, while also capturing key features near the Dirac point and predicting cut-off frequencies up to 143.5 GHz. Overall, SimulH offers a reliable and computationally efficient framework that can support the design and optimization of graphene-based RF and nanoelectronic devices. In this regard, SimulH contributes to computational nanotechnology by enabling scalable transport analysis in graphene-based nanoelectronics.

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Publication Details

Journal
Technologies
Published
2026-10-09
DOI
https://doi.org/10.3390/technologies14100652
Primary Topic
Graphene research and applications
Type
article
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article

SimulH: A Semiclassical Monte Carlo Framework for Transport Modeling in Monolayer Graphene Field-Effect Transistors

Edmundo Antonio Gutiérrez Domínguez, Agustín L. Herrera‐May, Enrique Delgado‐Alvarado, J. Martínez-Castillo et al.
Technologies
Graphene research and applications
article

SimulH: A Semiclassical Monte Carlo Framework for Transport Modeling in Monolayer Graphene Field-Effect Transistors

Edmundo Antonio Gutiérrez Domínguez, Agustín L. Herrera‐May, Enrique Delgado‐Alvarado, J. Martínez-Castillo, Pedro Javier Garcia-Ramirez, Modesto Herrera-González, Pedro Mabil-Espinosa
article en

Abstract

We present SimulH, a semiclassical Monte Carlo framework developed to model carrier transport in monolayer graphene field-effect transistors (GFETs), where achieving both physical accuracy and computational efficiency remains a key challenge for high-frequency device applications. The model is based on the Boltzmann transport equation and incorporates stochastic Monte Carlo simulations to describe carrier dynamics, including electron–phonon, electron–impurity, and electron–electron scattering processes, as well as quantum capacitance and contact resistance effects. To ensure a consistent description across operating conditions, three complementary approaches are used to evaluate the drain current. The results show strong agreement with reported experimental data, with prediction accuracies above 90% for mobility, capacitance behavior, and charge distribution. Simulations involving more than 40,000 carriers provide detailed insight into transport behavior and scattering mechanisms, while also capturing key features near the Dirac point and predicting cut-off frequencies up to 143.5 GHz. Overall, SimulH offers a reliable and computationally efficient framework that can support the design and optimization of graphene-based RF and nanoelectronic devices. In this regard, SimulH contributes to computational nanotechnology by enabling scalable transport analysis in graphene-based nanoelectronics.

TechnologiesVol. 14(10)
Universidad Veracruzana (MX), Instituto Tecnológico de Saltillo (MX)
Openalex Percentile: Top 28%
Graphene research and applications
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SimulH: A Semiclassical Monte Carlo Framework for Transport Modeling in Monolayer Graphene Field-Effect Transistors — Edmundo Antonio Gutiérrez Domínguez, Agustín L. Herrera‐May, et al. · Technologies (2026) | TGRS Research Map | TGRS