Data analytics and parallel-coordinate materials property charts

Jeffrey M Rickman

doi:10.1038/s41524-017-0061-8

Abstract

It is often advantageous to display material properties relationships in the form of charts that highlight important correlations and thereby enhance our understanding of materials behavior and facilitate materials selection. Unfortunately, in many cases, these correlations are highly multidimensional in nature, and one typically employs low-dimensional cross-sections of the property space to convey some aspects of these relationships. To overcome some of these difficulties, in this work we employ methods of data analytics in conjunction with a visualization strategy, known as parallel coordinates, to represent better multidimensional materials data and to extract useful relationships among properties. We illustrate the utility of this approach by the construction and systematic analysis of multidimensional materials properties charts for metallic and ceramic systems. These charts simplify the description of high-dimensional geometry, enable dimensional reduction and the identification of significant property correlations and underline distinctions among different materials classes.

Highlights

The mapping of material properties, pioneered by Ashby and coworkers, leads to the creation of charts that condense a large quantity of information into a useful representation that has the virtue of revealing important property correlations and that facilitates materials selection and design.[1,2] These charts form the basis of an optimized, systematic methodology for materials selection based on materials informatics
We illustrated the utility of combining the methods of data analytics with a parallel coordinates representation to construct and interpret multidimensional materials property charts
This paper illustrates the utility of combining higherdimensional data visualization with data analytics to quantify useful relationships among materials properties

Summary

INTRODUCTION

The mapping of material properties, pioneered by Ashby and coworkers, leads to the creation of charts that condense a large quantity of information into a useful representation that has the virtue of revealing important property correlations and that facilitates materials selection and design.[1,2] These (usually twodimensional) charts form the basis of an optimized, systematic methodology for materials selection based on materials informatics This program involves the identification of technical design requirements and the associated materials indices used for materials selection to meet these requirements.[3] The utility of material property charts is evidenced by their centrality in the materials selection process and, their ubiquity in engineering design courses. It has been shown that mathematical objects may be readily mapped from Cartesian to parallel coordinates, and that the latter coordinate system is wellsuited to multivariate statistical analysis.[12] Another example of an important duality is presented, which show that lines in a Cartesian coordinate system map into (polyline intersection) points in parallel coordinates. As will be seen below, when combined with data analytics, this approach constitutes a powerful tool for identifying important property relationships that can guide materials selection Table 1

RESULTS

DISCUSSION

METHODS