کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10672882 | 1010154 | 2019 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Non-destructive analysis on nano-textured surface of the vertical LED for light enhancement
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی مواد
فناوری نانو (نانو تکنولوژی)
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
In this work, the nano-textured surface of a GaN-based vertical light emitting diode (VLED) is characterized using a unified framework of non-destructive techniques (NDT) incorporating scanning electron microscopy (SEM), atomic force microscopy (AFM), Raman spectroscopy, Photoluminescence (PL), and X-ray diffraction (XRD) to optimize the light output efficiency. The surface roughness of â¼300â¯nm is revealed by AFM. Compressive stress-state of 0.667â¯GPa in the GaN surface is indicated by the E2(high) and A1(LO) phonon peak values at 569â¯cmâ1 and 736â¯cmâ1, respectively, in Raman spectrum and the wavelength at 442â¯nm rather 450â¯nm in PL spectrum. Without damaging the LED, surface analysis by NDT helps to advance the understanding of the optimized angular light redistribution subject to the high-roughness surface and the negative impacts of the stress induced at the top GaN layer, which leads to the optical efficiency degradation of the VLED. Furthermore, the impact of texturing on underneath n-GaN and MQWs layers is investigated via SEM-based transmission Kikuchi diffraction (TKD) and aberration-corrected scanning transmission electron microscopy (AC-STEM) and revealed a smooth surface morphology and good crystalline quality, indicating that the etch-induced damage by texture engineering does not impair the active region of the VLED. Accordingly, prospective optimizations are suggested in the context of surface engineering for light enhancement in VLEDs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ultramicroscopy - Volume 196, January 2019, Pages 1-9
Journal: Ultramicroscopy - Volume 196, January 2019, Pages 1-9
نویسندگان
Mansoor Ali Khan, Pengju Bian, Jiangtao Qu, Hansheng Chen, Hongwei Liu, Matthew Foley, Yin Yao, S.P. Ringer, Rongkun Zheng,