High-throughput powder diffraction. II. Applications of clustering methods and multivariate data analysis

Abstract

In high-throughput crystallography, it is possible to accumulate over 1000 powder diffraction patterns on a series of related compounds, often polymorphs. A method is presented that can analyse such data, automatically sort the patterns into related clusters or classes, characterize each cluster and identify any unusual samples containing, for example, unknown or unexpected polymorphs. Mixtures may be analysed quantitatively if a database of pure phases is available. A key component of the method is a set of visualization tools based on dendrograms, cluster analysis, pie charts, principal-component-based score plots and metric multidimensional scaling. Applications to pharmaceutical data and inorganic compounds are presented. The procedures have been incorporated into thePolySNAPcommercial computer software.