A sample-effective calibration design for multiple components.

The experimental design of mixtures for multivariate calibration is introduced. The idea of this design is based on uniform distribution of experimental points in a concentration hypercube. Unlike the already reported uniform designs this one is pretty simple and not computationally demanding. The suggested approach does not employ the concept of fixed "levels" and allows for designs with any number of experimental mixtures and any number of components depending on "time and money" considerations for each particular calibration experiment. The performance of the design is assessed with a UV-Vis spectroscopic experiment for simultaneous quantification of four inorganic components in complex mixtures. The performance of the PLS regression models derived from the design is compared with that of cyclic permutation and Kennard-Stone designs. The suggested approach allows for comparable or higher prediction accuracy with the lower number of experimental points.