3 predictions with data mining predictions is used to propose new virtual compounds, especially with higher order or multicomponent chemistries. Based on the prediction model, existing traditional structure maps of AB2N4 compounds are filled with spinel nitrides in chapter 5. Correlations between variables (or samples) in a created bigger library of binary and ternary compounds are visualized in the dimensionally reduced space in chapter 6. Through these activities, materials informatics will guide the choice of the most promising chemistries and identify correlations between variables. Chapter 7 presents the conclusions and future work. In the appendix, more detailed information about main machine learning techniques such as cluster analysis, principal component, and partial least squares is presented. The sequences of ‘Materials by design’ strategy based on materials informatics are summarized in Figure 1.1.
1.2
Research Background In the materials science community, crystallographic and thermochemical
databases historically have been two of the most well established databases. The former serves as the foundation for interpreting crystal structure data of metals, alloys and inorganic materials. The latter involves the compilation of fundamental thermochemical information in terms of heat capacity and calorimetric data. While crystallographic databases are primarily used as reference sources, thermodynamic databases were actually some of the earliest examples of informatics since these databases were integrated into thermochemical computations to map phase stability in binary and ternary alloys. This led the development of computationally derived phase diagrams which is a classic example of integrating information from databases and data models. The evolution of both databases has occurred independently although in terms of their scientific value, they are extraordinarily intertwined. Phase diagrams map out regimes of crystal structure in temperature-composition space or temperature-pressure space. Yet crystal structure databases were developed completely independently. At present the community has to work with each database separately, information searches are cumbersome, and data analysis interpretation involving both is very difficult to do.