Isolation of optimal compositions of single crystal superalloys by mapping of a material’s genome

Abstract The multicomponent composition space pertinent to the single crystal nickel-based superalloys is mapped and searched, using computational modelling. A resolution of 0.1 wt.% for the alloying elements is assumed, consistent with manufacturing practice. Databases are constructed of alloy compositions which are predicted to be of promising microstructural architecture: e.g. equal fractions of the γ and γ ′ phases. These may be regarded as maps – one might term them genomes – of this class of structural alloy. By combining the databases with additional composition-dependent property models, it is demonstrated that compositions can be identified which – subject to the accuracy and limitations of the sub-models – are likely to prove optimal, e.g. on the basis of their creep resistance, density and cost. The methods circumvent the need for the traditional empirically-driven approaches to alloy design.