Combinatorial approach for single-crystalline taon growth: Epitaxial β-Taon (100)/α-Al2O3 (012)

K. V.L.V. Narayanachari, D. Bruce Buchholz, Elise A. Goldfine, Jill K. Wenderott, Sossina M. Haile, Michael J. Bedzyk*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The photocatalyst β-TaON is of interest due to promising properties, such as stability, suitable band gap for visible light, and carrier mobility. We implemented a combinatorial, material discovery approach that used pulsed laser deposition (PLD) for thin-film growth, X-ray diffraction (XRD) for phase determination, and machine learning for data reduction. A lateral compositional gradient of TaOxNy was grown across the surface of an α-Al2O3 (012) wafer. After annealing, XRD scattering patterns were collected across the lateral gradient. Unsupervised machine learning separated the XRD data into four clusters (phases); one of which turned out to be the desired monoclinic β-TaON phase. Using high-resolution XRD, we determined that the β-TaON region of the film was a 260 Å thick single-crystal epitaxial with the substrate, having out-of-plane β-TaON (100)//α-Al2O3 (012) and in-plane β-TaON (010)//α-Al2O3 (210). X-ray reflectivity (XRR) analysis of the β-TaON region of the film showed an electron density matching that expected for β-TaON. X-ray photoelectron spectroscopy (XPS) showed a Ta5+ valence state in the β-TaON region of the film. This combinatorial approach, which produces a library of phases on a single wafer, proved to be very efficient for the growth of a material’s phase of interest.

Original languageEnglish (US)
Pages (from-to)3571-3576
Number of pages6
JournalACS Applied Electronic Materials
Issue number11
StatePublished - Nov 24 2020


  • Combinatorial synthesis
  • Machine learning
  • PLD
  • Thin film
  • XRD
  • β-TaON

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Materials Chemistry
  • Electrochemistry


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