Optical Modeling of a GaAs-Defect 1D Porous Silicon Photonic Crystal for High-Sensitivity γ-Ray Detection

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Abstract Radiation sensors are vital for applications in medical diagnostics, environmental monitoring, and nuclear safety. However, conventional sensors often suffer from limited sensitivity and poor operational stability. In this work, we theoretically propose a high-performance γ-ray radiation sensor based on a one-dimensional porous silicon photonic crystal (1D PhC) incorporating a gallium arsenide (GaAs) defect layer and porous silicon layers infiltrated with chalcogenide glass compositions (Se 70 S 30 ₋ x Sb x ). The sensing mechanism is governed by monitoring the shift in defect mode resonance within the photonic bandgap as a function of γ-ray dose (0-500 kGy). Dose dependent refractive index variations in the irradiated chalcogenide glasses were modeled using Bruggeman’s effective medium approximation and analyzed through the transfer matrix method (TMM) simulations. The proposed design offers structural simplicity, cost efficiency, and outstanding sensitivity, highlighting its strong potential for practical deployment in nuclear radiation detection, medical imaging, and industrial monitoring applications.
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Optical Modeling of a GaAs-Defect 1D Porous Silicon Photonic Crystal for High-Sensitivity γ-Ray Detection | 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 Optical Modeling of a GaAs-Defect 1D Porous Silicon Photonic Crystal for High-Sensitivity γ-Ray Detection Shaimaa El Shemy, Arafa Aly, Emad nady, Gaurav Malik, Heedae Kim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7926019/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Radiation sensors are vital for applications in medical diagnostics, environmental monitoring, and nuclear safety. However, conventional sensors often suffer from limited sensitivity and poor operational stability. In this work, we theoretically propose a high-performance γ-ray radiation sensor based on a one-dimensional porous silicon photonic crystal (1D PhC) incorporating a gallium arsenide (GaAs) defect layer and porous silicon layers infiltrated with chalcogenide glass compositions (Se 70 S 30 ₋ x Sb x ). The sensing mechanism is governed by monitoring the shift in defect mode resonance within the photonic bandgap as a function of γ-ray dose (0-500 kGy). Dose dependent refractive index variations in the irradiated chalcogenide glasses were modeled using Bruggeman’s effective medium approximation and analyzed through the transfer matrix method (TMM) simulations. The proposed design offers structural simplicity, cost efficiency, and outstanding sensitivity, highlighting its strong potential for practical deployment in nuclear radiation detection, medical imaging, and industrial monitoring applications. γ-ray radiation sensor Photonic crystals Porous silicon GaAs defect layer Transfer matrix method (TMM) Bruggeman effective medium approximation (BEMA) Optical dosimeter Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 20 Nov, 2025 Reviews received at journal 15 Nov, 2025 Reviews received at journal 06 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers invited by journal 04 Nov, 2025 Editor assigned by journal 30 Oct, 2025 Submission checks completed at journal 30 Oct, 2025 First submitted to journal 22 Oct, 2025 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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