Statistical methods can be applied to understanding and predicting crystallisation. Methods have been deduced to apply these techniques to problematic systems such as co-crystals and inorganic-organic hybrid materials.<br/>To use statistical approaches rigorously generally requires quite strictly defined experimental designs. While these designs are well understood, they are not necessarily practicable in terms of chemical properties for which we do not already have a solid understanding, for instance the problem of predicting outcomes in crystallisation experiments.One of the largest problems in this field is parameterising the chemical space; the methods of describing the systems such that statistical methods can apply, in particular the problem of keeping such descriptors invariant and mutually orthogonal. In addition, choosing the correct aspects of the system, that is those that demonstrate potential causal relationships, can prove to be challenging. This is because there is a plethora of means available to chemists to describe their systems. The application of statistical techniques such as decision trees and support vector machines has permitted the derivation of hypotheses and helped enhance understanding of crystallisation experiments, and this forms the presented work.

Crystal clear: Using statistical descriptions and analysis to understand crystallisation

251st National Meeting (2016)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.