Light Guide Layer Thickness Optimization for Enhancement of the Light Extraction Efficiency of Ultraviolet Light–Emitting Diodes

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Abstract Challenges related to deep-ultraviolet light-emitting diode substrates include material costs and lattice mismatch. Sapphire substrates are commonly used, although their high refractive index can result in the total internal reflection of light whereby some light is absorbed, reducing light extraction efficiency (LEE). In this study, we proposed an optimal thickness value of a sapphire substrate light guide layer through first-order optical design and used the optical simulation software Ansys SPEOS to assess and refine its effect on LEE. AlGaN ultraviolet-C light-emitting diode (UV-C LED) wafers with a substrate thickness of 150–700 μm were used. The simulation proceeded under a UV-C LED center wavelength of 275 nm to determine the optimal thickness of the light guide layer. Finally, the experimental results demonstrated that a light guide layer thickness of 150 μm resulted in a reference output power of 13.53 mW, and an increased thickness of 600 um resulted in output power of 20.58 mW. The LEE can therefore be increased by 1.52 times through light guide layer thickness optimization.
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Light Guide Layer Thickness Optimization for Enhancement of the Light Extraction Efficiency of Ultraviolet Light–Emitting Diodes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Light Guide Layer Thickness Optimization for Enhancement of the Light Extraction Efficiency of Ultraviolet Light–Emitting Diodes Zhi Ting Ye, Yuan Heng Cheng, Li Wei Hung, Kung Hsieh Hsu, Yu Chang Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-515794/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Challenges related to deep-ultraviolet light-emitting diode substrates include material costs and lattice mismatch. Sapphire substrates are commonly used, although their high refractive index can result in the total internal reflection of light whereby some light is absorbed, reducing light extraction efficiency (LEE). In this study, we proposed an optimal thickness value of a sapphire substrate light guide layer through first-order optical design and used the optical simulation software Ansys SPEOS to assess and refine its effect on LEE. AlGaN ultraviolet-C light-emitting diode (UV-C LED) wafers with a substrate thickness of 150–700 μm were used. The simulation proceeded under a UV-C LED center wavelength of 275 nm to determine the optimal thickness of the light guide layer. Finally, the experimental results demonstrated that a light guide layer thickness of 150 μm resulted in a reference output power of 13.53 mW, and an increased thickness of 600 um resulted in output power of 20.58 mW. The LEE can therefore be increased by 1.52 times through light guide layer thickness optimization. Nanoscience Mechanical Engineering Electrophysics Electrical Engineering Deep-ultraviolet light-emitting diode light extraction efficiency light guide layer firstorder optical design Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Full Text Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 27 May, 2021 Reviews received at journal 13 May, 2021 Reviewers invited by journal 13 May, 2021 Editor assigned by journal 12 May, 2021 First submitted to journal 10 May, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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