Adaptive Strategies for Materials Design using Uncertainties

Regression methods have provided a foundation for modeling structure-property relationships in materials science1,2,3,4,5,6. These methods take as input a data set of known material compositions along with some property (e.g. Each material, in turn, is described in terms of one or more features that represent aspects of structure, chemistry, bonding and/or microstructure in an abstract, high-dimensional space. The success of regression is based on its ability to capture the relative variation in a property as a function of the features, eventually culminating in the prediction of new materials with desired properties. Materials design is an optimization problem with the goal of maximizing (or minimizing) some desired property of a material, denoted by y, by varying certain features, denoted by x.