Analysis of the elemental effects on the surface potential of aluminum alloy using machine learning

Abstract Aluminum alloy contains intermetallic compounds, which contribute to the improvement of strength properties. However, when it is exposed a to a corrosive environment, the area around the compounds is dissolved preferentially, resulting in the formation of pitting corrosion. Although this dissolution reaction is presumed to be caused by the potential difference (Δ V ) between the matrix and the compounds, it has not been quantitatively clarified how Δ V is generated. In this article, we present our study on the effects of the compound composition on Δ V by using the technique of machine learning. The results showed that Δ V and the elemental concentration of the compounds have a linear relationship.