Rapid Screening of Molecular Beam Epitaxy Conditions for Monoclinic (InxGa1-x)2O3 Alloys

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Abstract

Molecular beam epitaxy is one of the highest quality growth methods, capable of achieving theoretical material property limits and unprecedented device performance. However, such ultimate quality usually comes at the cost of painstaking optimization of synthesis conditions and slow experimental iteration rates. Here we report on high-throughput molecular beam epitaxy with rapid screening of synthesis conditions using a novel cyclical growth and in-situ etch method. This novel approach leverages sub-oxide desorption present during molecular beam epitaxy and as such should be broadly applicable to other material systems. As a proof of concept, this method is applied to rapidly investigate the growth space for the ternary alloy (InxGa1-x)2O3 on (010) oriented ..beta..-Ga2O3 substrates using in-situ reflection high energy electron diffraction measurements. Two distinct growth regimes are identified and analyzed using machine learning image recognition algorithms, the first stabilizing a streaky 2x surface reconstruction typical of In-catalyzed ..beta..-Ga2O3 growth, and the second exhibiting a spotty/faceted pattern typical of phase separation. Targeted growth of (InxGa1-x)2O3 is performed under conditions near the boundary of the two regimes resulting in a 980 nm thick epitaxial layer with In mole fraction up to 5.6%. The cyclical growth/etch method retains the ~1 nm surface roughness of the single crystal substrate, increases experimental throughput approximately 6x, and improves single crystal substrate utilization by >40x. The high-throughput MBE method enables rapid discovery of growth regimes for ultra-wide bandgap oxide alloys for power conversion devices operating with high efficiency at high voltages and temperatures, as well as optical devices such as ultraviolet photodetectors.
Original languageAmerican English
Pages (from-to)5508-5519
Number of pages12
JournalJournal of Materials Chemistry A
Volume12
Issue number9
DOIs
StatePublished - 2024

NREL Publication Number

  • NREL/JA-5K00-88113

Keywords

  • alloy
  • gallium oxide
  • high throughput
  • machine learning
  • molecular beam epitaxy
  • quaternary
  • RHEED
  • ultra-wide bandgap

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