Multiphysics Simulation of Plasmonic Photoconductive Devices using Discontinuous Galerkin Methods
KAUST DepartmentComputational Electromagnetics Laboratory
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
KAUST Grant Number2016-CRG5-2953
Permanent link to this recordhttp://hdl.handle.net/10754/665176
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AbstractPlasmonic nanostructures significantly improve the performance of photoconductive devices (PCDs) in generating terahertz radiation. However, they are geometrically intricate and result in complicated electromagnetic (EM) field and carrier interactions under a bias voltage and upon excitation by an optical EM wave. These lead to new challenges in simulations of plasmonic PCDs, which cannot be addressed by existing numerical frameworks. In this work, a multiphysics framework making use of discontinuous Galerkin (DG) methods is developed to address these challenges. The operation of the PCD is analyzed in stationary and transient states, which are described by coupled systems of the Poisson and stationary drift-diffusion (DD) equations and the time-dependent Maxwell and DD equations, respectively. Both systems are discretized using DG schemes. The nonlinearity of the stationary system is accounted for using the Gummel iterative method while the nonlinear coupling between the time-dependent Maxwell and DD equations is tackled during time integration. The DG-based discretization and the explicit time marching help in handling space and time characteristic scales that are associated with different physical processes and differ by several orders of magnitude. The accuracy and applicability of the resulting multiphysics framework are demonstrated via simulations of conventional and plasmonic PCDs.
CitationChen, L., & Bagci, H. (2020). Multiphysics Simulation of Plasmonic Photoconductive Devices Using Discontinuous Galerkin Methods. IEEE Journal on Multiscale and Multiphysics Computational Techniques, 5, 188–200. doi:10.1109/jmmct.2020.3024265
SponsorsThis publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No 2016-CRG5-2953. The authors would like to thank the King Abdullah University of Science and Technology Supercomputing Laboratory (KSL) for providing the required computational resources.
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