Abstract

Many properties have been used to indicate the corrosion resistance of metallic materials. However, there is still no single property that can be used to compare across different alloy system and predict the corrosion resistance of metallic materials. Here, a universal scientifically based quantitative indicator called chloride susceptibility index (CSI) is introduced based on a multi-scale modeling framework. This framework can be applied to study the effect of different factors on corrosion resistance of alloys, including alloy composition, solution pH, Cl- concentration and temperature. Commonly used Ni-Cr-based alloys and stainless steels will be used as examples for this study. Firstly, ab initio modeling is used to study the adsorption energy of O and Cl to alloy surfaces with different solutes. Then, a Langmuir model is used to study the competitive adsorption of Cl vs. O under different conditions, from which CSI will be calculated. By connecting atomic scale properties with environmental conditions, CSI allows the predictable quantitative measurement of one aspect of the corrosion resistance of metallic materials, namely the sensitivity of the alloy surface to complexation with chloride versus oxide formation.

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