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Title: Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements
Authors: L.Hernández-Maya
Le ManhTu
Issue Date: 2022
Publisher: Elsevier
Abstract: This work presents a study on the correlation between the crystallographic texture and the pitting corrosion susceptibility of API 5L steels. The crystallographic textures of API 5L steel samples (codified as S1, S2, S3, and S4) were studied using EBSD measurements. A deterministic model based on symmetric spherical surface harmonics was proposed to describe the strong dependence of the pitting corrosion susceptibility on the crystallographic (grains) orientation of the (body-centered cubic) material. Using the model, pitting corrosion susceptibility index values estimated from EBSD raw data agreed in relative magnitudes (from sample to sample) with the predictions made from X-ray macrotexture measurements, and the results derived from other techniques such as cyclic polarization tests and analyses of SEM and AFM images. This agreement verified the capacity of EBSD to estimate the pitting corrosion susceptibility indices of carbon steels having different microstructures and textures, which were found to be 0.60, 0.53, 0.51, and 0.44 for S1, S2, S3, and S4, respectively. It was established that the higher the values of pitting corrosion susceptibility indices, the higher the tendency to present pitting corrosion of the material; thus, S1>S2>S3>S4. Moreover, the results have shown that the crystallographic texture plays a more decisive role in the behaviour of pitting corrosion in carbon steels compared to other microstructural and chemical parameters such as the grain size and inclusion content. The proposed (deterministic) model could be a novel tool for predicting pitting corrosion of the material, forming part of a novel method for the material selection process.
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