Micro-scale analysis method for structural composition of oxide on surface of reinforcing steel bar

By employing a sample preparation method involving layered cutting and inert protection, combined with various analytical techniques, a multi-dimensional correlation analysis of the oxide structure of reinforcing steel was achieved. This solved the problems of sample damage and inaccurate prediction in traditional analytical methods, and provided a reliable tool for assessing corrosion behavior.

CN120847156APending Publication Date: 2025-10-28HENAN ACADEMY OF SCI CHEM RES INST CO LTD
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Patent Information

Application Number
CN202510956149.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-11
Publication Date
2025-10-28

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Abstract

The invention relates to the technical field of material analysis, and discloses a reinforcing steel bar surface oxide structure composition microscale analysis method, which comprises the following steps: obtaining a high-fidelity sample through a layered inert protection sample preparation technology, and sequentially analyzing oxide microstructure and element distribution by adopting a scanning electron microscope-energy spectrum coupling technology, atomic-scale crystal defect observation is realized by combining a spherical aberration correction transmission electron microscope, macroscopic phase composition and microcell chemical valence information are respectively acquired synchronously through X-ray diffraction and X-ray photoelectron spectroscopy, and finally a cross-scale correlation model covering morphological characteristics, crystal structures, phase distribution and chemical states is constructed through multi-source data fusion. And micro-scale structure analysis is realized. Through combination of a multi-source characterization technology, steel bar oxide cross-scale analysis is realized, a high-fidelity sample preparation technology is adopted to guarantee an original state of a sample, a chloride ion diffusion quantitative model fused with crystal defect parameters is constructed, and rust layer protection evaluation is improved from qualitative observation to quantitative prediction.
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