The aim of this work is to simulate the charge transport in a monolayer graphene on a substrate. This requires the inclusion of the scatterings of the charge carriers with the impurities and the phonons of the substrate, besides the interaction mechanisms already present in the graphene layer. As physical model, the semiclassical Boltzmann equation will be assumed. Two approaches will be used for the simulations: a numerical scheme based on the Discontinuous Galerkin method for finding deterministic (non stochastic) solutions and a new Direct Monte Carlo Simulation formulated in Romano et al. (J Comput Phys 302:267–284, 2015) in order to deal in the appropriate way with the Pauli exclusion principle for degenerate Fermi gases. A cross validation of the deterministic and stochastic solutions shows the robustness and accuracy of both the approaches.

Cross validation of discontinuous Galerkin method and Monte Carlo simulations of charge transport in graphene on substrate / Coco, M.; Majorana, A.; Romano, V.. - In: RICERCHE DI MATEMATICA. - ISSN 0035-5038. - 66:1(2017), pp. 201-220. [10.1007/s11587-016-0298-4]

Cross validation of discontinuous Galerkin method and Monte Carlo simulations of charge transport in graphene on substrate

Coco M.
Primo
;
2017-01-01

Abstract

The aim of this work is to simulate the charge transport in a monolayer graphene on a substrate. This requires the inclusion of the scatterings of the charge carriers with the impurities and the phonons of the substrate, besides the interaction mechanisms already present in the graphene layer. As physical model, the semiclassical Boltzmann equation will be assumed. Two approaches will be used for the simulations: a numerical scheme based on the Discontinuous Galerkin method for finding deterministic (non stochastic) solutions and a new Direct Monte Carlo Simulation formulated in Romano et al. (J Comput Phys 302:267–284, 2015) in order to deal in the appropriate way with the Pauli exclusion principle for degenerate Fermi gases. A cross validation of the deterministic and stochastic solutions shows the robustness and accuracy of both the approaches.
2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/299711
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