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Updated: Aug 30, 2025

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Determining Tribocorrosion Rate and Wear-Corrosion Synergy of Bulk and Thin Film Aluminum Alloys
Published on: September 11, 2018
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Correlation among Composition, Microstructure and Hardness of 7xxx Aluminum Alloy Using Original Statistical
Bing Han1,2, Dandan Sun1, Weihao Wan2
1Qingdao NCS Testing & Corrosion Protection Technology Co., Ltd., Qingdao 266071, China.
Materials (Basel, Switzerland)
|August 26, 2022
Summary
Understanding material composition, microstructure, and properties is key. This study reveals how elemental segregation and recrystallization influence hardness in materials, identifying zones of low hardness.
Area of Science:
- Materials Science
- Metallurgy
- Physical Chemistry
Background:
- The relationship between material composition, microstructure, and properties is crucial for material enhancement.
- High-throughput testing enables detailed analysis of material characteristics.
Purpose of the Study:
- To quantitatively analyze the correlation between material composition, microstructure, and hardness.
- To investigate the distribution characteristics and rules within material data sets.
Main Methods:
- Utilized high-throughput testing to obtain continuous data on elemental composition, recrystallization, hardness, and undissolved phase distribution.
- Established data mapping between multi-source heterogeneous micro-areas for correlation analysis.
- Analyzed distribution characteristics of single data sets and micro-area data.
Main Results:
- The average size of the insoluble phase was larger in the material's center than the surface, with central segregation causing an abnormal decrease in T4 insoluble phase area.
- Positive micro-segregation of Al, Cr, Ti, and Zr, and negative micro-segregation of Zn, Cu, and Fe were observed in T5 recrystallized grains.
- Insoluble phase growth was synchronous with recrystallization proportion and recrystallized grain size.
Conclusions:
- Composition segregation and recrystallized coarse grains are the primary causes for low hardness zones in T4 and T5 materials, respectively.
- Microstructural features significantly impact material properties like hardness.
Keywords:
7B05 aluminum alloydata miningdeep learningelement distributionrecrystallizationspatial-mapping
