腐蚀
材料科学
Rust(编程语言)
冶金
合金
图层(电子)
耐候钢
扫描电子显微镜
拉曼光谱
合金钢
锡
复合材料
光学
物理
计算机科学
程序设计语言
作者
Lijun Yang,Xiaojia Yang,Feifan Xu,Qing Li,Ronggui Zhu,Xuequn Cheng,Guowei Yang,Yong Li
标识
DOI:10.1016/j.conbuildmat.2023.133029
摘要
This study investigates the formation and properties of rust layers on low alloy steel containing 0.40 wt% tin (Sn) in rural atmospheric environments. The rust layer was analyzed using various techniques, including scanning electron microscopy, X-ray diffraction and Raman spectroscopy. Additionally, a new corrosion big data sensor was used to evaluate the corrosion resistance of Sn-containing low alloy steels. Results show that the presence of Sn in the low alloy steel positively affects corrosion resistance, resulting in the formation of a denser and more protective rust layer. The corrosion big data technology is a precise and intuitive approach for identifying the subtle impact of Sn on the corrosion resistance of low alloys. These findings offer insights into the mechanisms behind the corrosion resistance of low alloy steels in rural atmospheric environments and highlight the potential of Sn as an effective alloying element for improving the corrosion resistance of such structural materials.
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