Document Type
Article
Publication Date
1-1-2023
Abstract
Bulk AlN single crystal has a great demand as a substrate material for AlGaN-based optical and electronic devices such as deep ultraviolet light-emitting diodes and high-power transistors. We have previously proposed a novel solution-growth method using Ni–Al solution with an in-situ observation system for solution growth of AlN crystal using electromagnetic levitation. In this paper, to investigate AlN formation behavior on 40 mol%Al–Ni droplets, two precisely synchronized high-speed cameras from the horizontal and vertical directions were installed. AlN formation behavior was evaluated quantitatively using computer vision image processing techniques. Based on the results, we demonstrated the growth of thick AlN film at 2030 K for 1 h. A 3.8-μm-thick c-axis oriented AlN film successfully formed on the droplet, and the film was also oriented in-plane. The + c-direction AlN film grew towards the droplet center from the surface by reacting dissolved nitrogen and Al atoms.
Keywords
aluminum nitride, computer vision image processing, in-situ observation, solution growth, thermodynamics
Language
English
Publication Title
Materials Science in Semiconductor Processing
Grant
20H02633
Rights
© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/BY-NC-ND/4.0/), which permits non-commercial copying and redistribution of the material in any medium or format, provided the original work is not changed in any way and is properly cited.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Masayoshi Adachi, Sonoko Hamaya, Daisuke Morikawa, Benjamin G. Pierce, Ahmad M. Karimi, Yuji Yamagata, Kenji Tsuda, Roger H. French, Hiroyuki Fukuyama, Temperature dependence of crystal growth behavior of AlN on Ni–Al using electromagnetic levitation and computer vision technique, Materials Science in Semiconductor Processing, Volume 153, 2023, 107167, ISSN 1369-8001, https://doi.org/10.1016/j.mssp.2022.107167.
Manuscript Version
Final Publisher Version