Multivariate curve resolution methods and the design of experiments

A major problem of multivariate curve resolution methods is the underlying non-uniqueness of the pure component decompositions. This raises the question how a chemical experiment should be designed so that the solution ambiguity is as small as possible. Changes of the reaction conditions belong to the possible variations whereas for a fixed chemical reaction system, the pure component spectra appear to be unchangeable. The paper investigates and discusses the possibility to design a chemical experiment in a way that minimizes the ambiguity of the factorization. The analysis identifies regions of the spectra that are responsible for a small ambiguity. Certain sources are identified that are responsible for an increased ambiguity by means of an a posteriori analysis. This results in recommendations how to construct spectral measurements incorporating a reduced factorization ambiguity. Furthermore, lower bounds on an unavoidable base level of ambiguity are specified under the constraint of fixed reactants. The problem analysis is accompanied by investigations of several experimental data sets.