12th International Conference on Zinc & Zinc Alloy Coated Steel Sheet - GALVATECH 2021

New generation advanced high strength steels (AHSS) are utilized in automobiles to reduce weight while enhancing fuel efficiency and crash performance. Zn-based coatings are commonly applied on sheet steels to achieve sacrificial corrosion protection. Galvanizing of AHSS is challenging due to the relatively high application temperature of these coatings (460 °C for hot-dip galvanizing). High application temperatures may affect the microstructure and resulting mechanical properties of the substrate AHSS. New coatings with significantly lower melting points and acceptable corrosion resistance would enable new substrate processing alternatives. From a design perspective, this presents an exciting optimization challenge with respect to identifying chemistries in multi-component space that simultaneously satisfy multiple performance criteria. Traditional materials development, starting from research to commercialization, typically takes 10-20 years. This work presents a new approach through a combination of computational and data-driven efforts for accelerating the development of the novel coating alloys. In this study, machine-learning (ML) algorithms trained on i) existing corrosion data and ii) computed liquid/solid phase stabilities are used to optimize the synthesis of novel coating alloys. The ML models are used to predict corrosion current, corrosion potential, and melting temperature of the coatings in high-dimensional Zn-Mg-Al-Sn alloy space. The ML models are also applied to find feature correlations and to predict new coating alloy compositions with enhanced corrosion resistance for specified conditions of the corrosion environment.