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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Figure CN120847156A_ABST
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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