Abstract

Gallium Nitride (GaN) is becoming increasingly more attractive for a wide range of applications, such as optoelectronics, wireless communication, automotive and power electronics. Switching GaN diodes are becoming indispensable for power electronics due to their low on-resistance and capacity to withstand high voltages. A great deal of research has been done on GaN diodes over the decades but a major issue with previous studies is the lack of explicit inclusion of electron-electron interaction, which can be quite important for high carrier densities encountered. Here we consider this electron-electron interaction, within a non-parabolic band scheme, as the first attempt at including such effects when modeling nitride devices. Electron-electron scattering is treated using a real space molecular dynamics approach, which exactly models this interaction within a semi-classical framework. It results in strong carrier-carrier scattering on the biased contact of the resistor, where rapid carrier relaxation occurs.

Original languageEnglish (US)
Title of host publicationLarge-Scale Scientific Computing - 6th International Conference, LSSC 2007, Revised Papers
Pages131-138
Number of pages8
DOIs
StatePublished - Dec 1 2008
Event6th International Conference on Large-Scale Scientific Computing, LSSC 2007 - Sozopol, Bulgaria
Duration: Jun 5 2007Jun 9 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4818 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Large-Scale Scientific Computing, LSSC 2007
CountryBulgaria
CitySozopol
Period6/5/076/9/07

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Ashok, A., Vasileska, D., Hartin, O., & Goodnick, S. (2008). Monte Carlo simulation of GaN diode including intercarrier interactions. In Large-Scale Scientific Computing - 6th International Conference, LSSC 2007, Revised Papers (pp. 131-138). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4818 LNCS). https://doi.org/10.1007/978-3-540-78827-0_13