AUTHOR=Xu Dasen , Kang Huaipu , Qiao Liang , Chen Haoyu , Tang Tiegang , Ren Guowu , Chen Yongtao 

TITLE=Integrated diagnostic analysis of ejecta from lead with micro-defects under detonation loading

JOURNAL=Frontiers in Physics

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2025.1514389

DOI=10.3389/fphy.2025.1514389

ISSN=2296-424X

ABSTRACT=IntroductionUnderstanding ejecta generation from lead under detonation is critical for applications requiring high-strain-rate material performance. However, conventional single-method diagnostics often struggle to capture both high-density and low-density ejecta accurately, particularly in low-melting-point metals where phase transitions complicate measurements.MethodsTo address these challenges, we integrated three advanced diagnostics—photonic Doppler velocimetry (PDV), an improved Asay-F window, and high-speed X-ray imaging. Lead samples with micro-defects were explosively loaded, creating shock-induced spallation and fragmentation. PDV provided high-resolution velocity data, while the Asay-F window captured ejecta density at multiple radial locations. Concurrently, high-speed X-ray imaging offered two-dimensional density distributions, which were processed via Abel inversion to obtain three-dimensional ejecta profiles.ResultsThe combined approach successfully resolved both dense and sparse ejecta layers, revealing complex velocity gradients ranging up to nearly 3000 m/s and indicating localized tensile failures driven by micro-defects. The Asay-F window measurements showed density transitions from as low as 0.2% to over 1% of solid lead, corroborated by X-ray-derived data. Notably, spatial analysis indicated layered fragmentation governed by wave interactions, distinguishing planar from spherical shock contributions.DiscussionBy leveraging the complementary strengths of PDV, Asay-F window, and X-ray diagnostics, this study achieves a comprehensive characterization of ejecta formation in shock-loaded lead. The reliable correlation among velocity, density, and spatial morphology not only validates dynamic failure models but also enables refined insights into micro-defect–driven fragmentation. These findings advance diagnostic capabilities for detonation-driven phenomena and provide a robust framework for designing materials and protective systems under extreme conditions.