Monte Carlo Particle Simulation for Electrical and Thermal Analysis of a MESFET using the Finite-Element Approach
Abstract
Particle simulations based on the Boltzmann Transport Equation (BTE) and the Monte Carlo method are a powerful tool for studying semiconductor devices in the nanometer to submicrometer regime. As with most numerical solvers, particle simulations require a mesh to solve for the fields within a semiconductor device. Traditionally, particle simulations use a finite-difference method (FDM) on a mesh with uniform step sizes. This work explores using a finite-element method (FEM) with a non-uniform triangular mesh. The FEM is validated by comparing results back to those obtained by using the FDM, for the simple example of a GaAs MESFET. And the FEM runs ten times faster than the FDM. Aside from electrical aspects of the device, heat flow within the device is also studied using the finite-element approach.
Recommended Citation
Z. Sun et al., "Monte Carlo Particle Simulation for Electrical and Thermal Analysis of a MESFET using the Finite-Element Approach," Proceedings of the 2019 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (2019, Boston, MA), Institute of Electrical and Electronics Engineers (IEEE), May 2019.
The definitive version is available at https://doi.org/10.1109/NEMO.2019.8853747
Meeting Name
2019 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2019 (2019: May 29-31, Boston, MA)
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Electromagnetic Compatibility (EMC) Laboratory
Keywords and Phrases
Boltzmann Transport Equation; Finite-Difference; Finite-Element; MESFET; Monte Carlo; Particles
International Standard Book Number (ISBN)
978-153869516-6
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 May 2019
Comments
This work was partially supported by the National Science Foundation under Grant IIP-1440110.