Optimization of Surface Texturing and Reflector Geometry in AlGaN-Based Deep Ultraviolet Light Emitting Diode Using Monte-Carlo Ray-tracing method

Abstract

The research presents on optimizing the light extraction efficiency of Deep Ultraviolet Light Emitting Diodes (DUV LEDs) remains a critical challenge due to severe optical losses. AlGaN DUV LEDs are essential for sterilization and biomedical applications; however, their efficiency is severely limited by high reflection, absorption, and scattering losses. Light Extraction Efficiency (LEE) and External Quantum Efficiency (EQE) are targeted for improvement by optimizing the LED package structure. Using Monte-Carlo ray-tracing method, the simulation models photon paths including reflections, refractions, and absorptions while considering spectral refractive indices and surface roughness. Light-trapping mechanisms caused by Total Internal Reflection (TIR) are identified, and the impacts of various reflectors, such as Metallic, Distributed Bragg (DBR), and Omni-Directional Reflectors (ODR), are evaluated in this investigation. A framework for optimizing layer thickness and surface textures to achieve a directional radiation pattern and higher output power is established through these findings, supporting commercial DUV LED applications.