JOURNAL ARTICLE
Observation of structural defects in GaN/InGaN multi-quantum wells grown on semipolar (112¯2) substrate using cathodoluminescence in transmission electron microscopy.
Published In: Journal of Vacuum Science & Technology: Part A-Vacuums, Surfaces & Films, 2024, v. 42, n. 2. P. 1 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Sheen, Mi-Hyang; Lee, Yong-Hee; Nam, Okhyun; Kim, Young-Woon 3 of 3
Abstract
This article focuses on the characterization of defect structures, specifically basal plane stacking faults (BSFs), in semipolar (11̅22) gallium nitride (GaN) thin films grown on m-plane sapphire substrates for light-emitting diode (LED) applications. Using transmission electron microscopy cathodoluminescence (TEM-CL), the study identifies and maps the distribution of three BSF types—I1, I2, and E—along with related partial dislocations (PDs) and prismatic stacking faults (PSFs), revealing that I1-BSFs are the most prevalent while I2-BSFs appear as thinner strips with lower density. The research highlights how these defects influence luminescence properties and surface morphology, with TEM-CL providing high spatial resolution to distinguish defect types and their optical signatures, which are challenging to resolve by conventional methods. The findings also discuss the impact of hemispherical patterned sapphire substrates (HPSS) on defect formation and suggest that this optical fingerprinting approach can aid in optimizing growth processes to improve LED efficiency on semipolar GaN films.
Additional Information
- Source:Journal of Vacuum Science & Technology: Part A-Vacuums, Surfaces & Films. 2024/03, Vol. 42, Issue 2, p1
- Document Type:Article
- Subject Area:Science
- Publication Date:2024
- ISSN:07342101
- DOI:10.1116/6.0003232
- Accession Number:175796218
- Copyright Statement:Copyright of Journal of Vacuum Science & Technology: Part A-Vacuums, Surfaces & Films is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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