Gallium Nitride Depth Porosity Using Image Processing Method

• Published in: 13th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2023
• Main Author: Fauzi N.A.; Isa I.S.; Isa S.M.; Manaf A.A.; Rahim A.F.A.; Mahmood A.; Noordin I.R.M.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165208702&doi=10.1109%2fISCAIE57739.2023.10165126&partnerID=40&md5=b2cdd7a3ad40d0b8fbc40ba9bd3ba878

Porous Gallium Nitride (GaN) structure is commonly prepared by using direct current photo-assisted electrochemical etching (DC-PECE) technique to generate porous structure. However, to reach a generalized pores depth porosity measured using conventional methods is impossible due to the complex and very thin layer of the GaN structure. Image processing has been widely used in validating the measurement and may be significant for this application. This study is aimed to propose a recent method to measure pores depth porosity using image processing techniques. Porosity of the structures obtained by calculating the areas occupied by the pores. To validate the method, the evaluation of porous GaN quality is performed through a non-destructive investigation of its nanostructures using adapting image analysis techniques. The quantitative results showed good agreement between measurement and calculation (percentage porosity and pore depth) based on the image-processing data with 91 % and 78 % correlation coefficient. © 2023 IEEE.