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电化学噪声分析:一种评估不同材料中各方法有效性的方法。

Electrochemical Noise Analysis: An Approach to the Effectivity of Each Method in Different Materials.

作者信息

Jáquez-Muñoz Jesús Manuel, Gaona-Tiburcio Citlalli, Méndez-Ramírez Ce Tochtli, Martínez-Ramos Cynthia, Baltazar-Zamora Miguel Angel, Santiago-Hurtado Griselda, Estupinan-Lopez Francisco, Landa-Ruiz Laura, Nieves-Mendoza Demetrio, Almeraya-Calderon Facundo

机构信息

Universidad Autónoma de Ciudad Juárez, Ciudad Juárez 32315, Mexico.

Centro de Investigación e Innovación en Ingeniería Aeronáutica (CIIIA), Universidad Autónoma de Nuevo León FIME, San Nicolás de los Garza 66455, Mexico.

出版信息

Materials (Basel). 2024 Aug 12;17(16):4013. doi: 10.3390/ma17164013.

DOI:10.3390/ma17164013
PMID:39203191
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11355995/
Abstract

Corrosion deterioration of materials is a major problem affecting economic, safety, and logistical issues, especially in the aeronautical sector. Detecting the correct corrosion type in metal alloys is very important to know how to mitigate the corrosion problem. Electrochemical noise (EN) is a corrosion technique used to characterize the behavior of different alloys and determine the type of corrosion in a system. The objective of this research is to characterize by EN technique different aeronautical alloys (Al, Ti, steels, and superalloys) using different analysis methods such as time domain (visual analysis, statistical), frequency domain (power spectral density (PSD)), and frequency-time domain (wavelet decomposition, Hilbert Huang analysis, and recurrence plots (RP)) related to the corrosion process. Optical microscopy (OM) is used to observe the surface of the tested samples. The alloys were exposed to 3.5 wt.% NaCl and HSO solutions at room temperature. The results indicate that HHT and recurrence plots are the best options for determining the corrosion type compared with the other methods due to their ability to analyze dynamic and chaotic systems, such as corrosion. Corrosion processes such as passivation and localized corrosion can be differentiated when analyzed using HHT and RP methods when a passive system presents values of determinism between 0.5 and 0.8. Also, to differentiate the passive system from the localized system, it is necessary to see the recurrence plot due to the similarity of the determinism value. Noise impedance (Z) is one of the best options for determining the corrosion kinetics of one system, showing that Ti CP2 and Ti-6Al-4V presented 742,824 and 939,575 Ω·cm, while R presented 271,851 and 325,751 Ω·cm, being the highest when exposed to HSO.

摘要

材料的腐蚀劣化是一个影响经济、安全和后勤问题的主要问题,尤其是在航空领域。检测金属合金中正确的腐蚀类型对于了解如何减轻腐蚀问题非常重要。电化学噪声(EN)是一种用于表征不同合金行为并确定系统中腐蚀类型的腐蚀技术。本研究的目的是使用不同的分析方法,如时域(视觉分析、统计)、频域(功率谱密度(PSD))以及与腐蚀过程相关的频率-时域(小波分解、希尔伯特-黄分析和递归图(RP)),通过EN技术对不同的航空合金(铝、钛、钢和超级合金)进行表征。光学显微镜(OM)用于观察测试样品的表面。这些合金在室温下暴露于3.5 wt.%的NaCl和HSO溶液中。结果表明,与其他方法相比,希尔伯特-黄变换(HHT)和递归图是确定腐蚀类型的最佳选择,因为它们能够分析动态和混沌系统,如腐蚀。当使用HHT和RP方法进行分析时,对于呈现0.5至0.8之间确定性值的被动系统,钝化和局部腐蚀等腐蚀过程可以区分开来。此外,由于确定性值的相似性,有必要查看递归图以区分被动系统和局部系统。噪声阻抗(Z)是确定一个系统腐蚀动力学的最佳选择之一,结果表明,Ti CP2和Ti-6Al-4V的噪声阻抗分别为742,824和939,575 Ω·cm,而R的噪声阻抗分别为271,851和325,751 Ω·cm,在暴露于HSO时为最高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/1626fd624b42/materials-17-04013-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/7f5390c9a06e/materials-17-04013-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/73dab69ecc7c/materials-17-04013-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/40fce8bcb1ad/materials-17-04013-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/4a4144992192/materials-17-04013-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/d95b6b433ea4/materials-17-04013-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/ff22f7210738/materials-17-04013-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/1833c1b0ee96/materials-17-04013-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/09c8d356769a/materials-17-04013-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/ad48f703982b/materials-17-04013-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/1626fd624b42/materials-17-04013-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/7f5390c9a06e/materials-17-04013-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/73dab69ecc7c/materials-17-04013-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/40fce8bcb1ad/materials-17-04013-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/4a4144992192/materials-17-04013-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/d95b6b433ea4/materials-17-04013-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/ff22f7210738/materials-17-04013-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/1833c1b0ee96/materials-17-04013-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/09c8d356769a/materials-17-04013-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/ad48f703982b/materials-17-04013-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/267b/11355995/1626fd624b42/materials-17-04013-g010.jpg

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