Robust Zeff-Mapping in Composites via Joint Beam-Hardening and Detector- Response Correction

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This preprint studied robust effective atomic number (Zeff) mapping in X-ray projection imaging for composite materials, using an approach that integrates a folded energy spectrum model capturing joint beam-hardening from a composite X-ray source and detector-response matrix effects. It builds a response-corrected spectral database via Monte Carlo simulation, linearizes nonlinear attenuation curves with the Spectral Mass-Attenuation Linearisation (SMAL) method, and performs weighted least-squares spectral matching to invert Zeff, reporting experimental standard-material performance with inversion error controlled within ±0.2. It also demonstrates defect detection in carbon fiber composites by distinguishing samples with similar grey levels but different compositions. The paper focuses on X-ray spectral imaging and does not discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract The quantitative analysis of the effective atomic number in X-ray projection imaging is constrained by beam hardening effects and nonlinear spectral distortion induced by detector response. To address these limitations, this paper proposes a composite correction method for thickness-decoupled effective atomic number inversion. The method establishes a folded energy spectrum model integrating the attenuation characteristics of a composite X-ray source with detector response matrices, and a response-corrected spectral database for materials with different atomic numbers is established through Monte Carlo simulation. The Spectral Mass-Attenuation Linearisation (SMAL) method is employed to map nonlinear attenuation curves onto a unified linear domain, followed by weighted least-squares spectral matching to perform effective atomic number () inversion. Experimental results obtained using standard materials demonstrate that the proposed method achieves high quantitative accuracy in effective atomic number estimation, with the inversion error controlled within ± 0.2. In defect detection applications for carbon fibre composites, the method clearly distinguishes samples with similar grey levels but different compositions, highlighting its practical value in non-destructive testing.
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Robust Zeff-Mapping in Composites via Joint Beam-Hardening and Detector- Response Correction | 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 Article Robust Z eff -Mapping in Composites via Joint Beam-Hardening and Detector- Response Correction Yuetong Zhao, Jie Zhang, Xin Yan, Yiheng Liu, Gang Wang, Kai He, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9222359/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract The quantitative analysis of the effective atomic number in X-ray projection imaging is constrained by beam hardening effects and nonlinear spectral distortion induced by detector response. To address these limitations, this paper proposes a composite correction method for thickness-decoupled effective atomic number inversion. The method establishes a folded energy spectrum model integrating the attenuation characteristics of a composite X-ray source with detector response matrices, and a response-corrected spectral database for materials with different atomic numbers is established through Monte Carlo simulation. The Spectral Mass-Attenuation Linearisation (SMAL) method is employed to map nonlinear attenuation curves onto a unified linear domain, followed by weighted least-squares spectral matching to perform effective atomic number ( ) inversion. Experimental results obtained using standard materials demonstrate that the proposed method achieves high quantitative accuracy in effective atomic number estimation, with the inversion error controlled within ± 0.2. In defect detection applications for carbon fibre composites, the method clearly distinguishes samples with similar grey levels but different compositions, highlighting its practical value in non-destructive testing. Physical sciences/Engineering Physical sciences/Materials science Physical sciences/Optics and photonics Physical sciences/Physics X-ray spectral imaging Z-mapping beam hardening detector response composite materials Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 13 May, 2026 Reviews received at journal 12 May, 2026 Reviews received at journal 06 May, 2026 Reviewers agreed at journal 16 Apr, 2026 Reviewers agreed at journal 16 Apr, 2026 Reviewers invited by journal 15 Apr, 2026 Editor invited by journal 30 Mar, 2026 Editor assigned by journal 26 Mar, 2026 Submission checks completed at journal 26 Mar, 2026 First submitted to journal 25 Mar, 2026 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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