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ELO-compatible back reflectors for light management in thin-film GaAs-based LEDs

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DataCite Commons2025-11-26 更新2026-05-04 收录
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https://data.ru.nl/collections/ru/imm/ams2025_03_dsc_569
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With the advent of thermophotonics, interest in GaAs-based light-emitting diodes (LEDs) has recently reignited due to their potential in energy conversion applications, including the demonstration of electroluminescent cooling (ELC). To that end, the light extraction efficiency of these devices should ultimately approach unity to achieve the necessary high external quantum efficiency. This work therefore evaluates various back reflector designs on GaAs/InGaP shifted double heterojunction LEDs produced by epitaxial lift-off (ELO), targeting reduced back-side losses and improved front-side light extraction. Through optical and electrical characterization of the LEDs, the optimal back reflector design in this work was found to combine a texturing technique previously employed in ultra-thin GaAs solar cells with an omnidirectional reflector based on ZnS and Ag. This approach yields an approximately twofold enhancement in external quantum efficiency compared to a planar Ag reflector, corresponding to a tenfold improvement over comparable substrate-based LEDs. These enhancements are thoroughly analyzed in terms of the probabilities of escape and reabsorption, calculated using our in-house developed Photon Dynamics model. This model suggests that a further fourfold enhancement could be ach ieved by integrating a high-refractive index ZnSe dome, optimizing the rear-side dielectric, and improving the haze in reflection of the textured reflector. Beyond the potential for GaAs-based LEDs in demonstrating ELC, these advancements contribute to the broader development of thermophotonic energy conversion systems. Additionally, the presented ELO-compatible textured omnidirectional reflector offers broad applicability to III-V optoelectronic devices, including LEDs for the lighting and display industry, thermophotovoltaic devices, and ultra-thin solar cells. This dataset contains raw data obtained from measurements used to produce the figures in the publication, the figures themselves, Matlab scripts that were used for calculations, and experimental protocols.
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Radboud University
创建时间:
2025-09-25
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