MRS Meetings and Events

 

EQ01.06.09 2022 MRS Spring Meeting

Increasing the Power-Electronics Figure of Merit of AlGaN with Atomically Thin Superlattices

When and Where

May 11, 2022
10:45am - 11:00am

Hawai'i Convention Center, Level 3, 318B

Presenter

Co-Author(s)

Nick Pant1,Woncheol Lee1,Nocona Sanders1,Emmanouil Kioupakis1

University of Michigan1

Abstract

Nick Pant1,Woncheol Lee1,Nocona Sanders1,Emmanouil Kioupakis1

University of Michigan1
Alloying GaN with Al increases the band gap but decreases the electron mobility due to alloy scattering. Using predictive first-principles calculations, we find that Al compositions greater than 75% are required to obtain even a two-fold increase of the Baliga Figure of Merit (BFOM) compared to GaN. At such high compositions, shallow donors undergo the DX transition making impurity doping difficult without severely limiting the mobility. Electrons in atomically ordered compounds do not undergo alloy scattering, therefore a large increase in the figure of merit may be possible for lower Al compositions where impurity doping is efficient. Atomically thin, chemically ordered superlattices of AlN and GaN have been known to grow experimentally under appropriate growth conditions. Using many-body perturbation theory and density functional perturbation theory, we uncover the electronic properties of atomically thin AlN/GaN superlattices with an Al to Ga ratio of 1:1, corresponding to 50% Al composition. We predict band gaps up to 4.91 eV and in-plane mobility that is up to 3x higher than that of random Al<sub>0.5</sub>Ga<sub>0.5</sub>N. Using a modified BFOM that accounts for the dopant activation energy, we predict that atomically thin AlN/GaN superlattices have the highest modified BFOM among several prominent ultra-wide band-gap materials, including GaN, AlN, random AlGaN, β-Ga2O3, cBN, and diamond.

Keywords

electron-phonon interactions | nitride

Symposium Organizers

Robert Kaplar, Sandia National Laboratories
Srabanti Chowdhury, Stanford University
Yoshinao Kumagai, Tokyo University of Agriculture and Technology
Julien Pernot, University of Grenoble Alpes

Publishing Alliance

MRS publishes with Springer Nature