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Abstract

A novel modeling strategy, which combines artificial intelligence (AI) with artificial materials (AM) will be proposed and called Artificial Materials Intelligence (AMI). Established physical laws, cross-correlations between different materials properties and well developed thermodynamic databases will be considered during the development and application of AMI. Machine learning will be used if the established physical basis is insufficient for predictive materials models. The application of such combined methodology allows keeping as much physics as possible on the one side and reducing the number of exploratory variables and required data on the other. The proposed study demonstrates the applicability of high-throughput simulations and physically-based data-driven modelling strategy combined in AMI to predict mechanical properties of complex, microstructure dominated materials, such as Ni- and Co-based super alloys, and to accelerate discovery of optimal chemical composition for these alloys.