Fluorescence spectroscopy and multivariate spectral descriptor analysis for high-throughput multiparameter optimization of polymerization conditions of combinatorial 96-microreactor arrays.

Abstract

Selection of optimum process conditions in combinatorial microreactors is essential if the combinatorial synthesis process is to be correlated with the synthesis process on a more conventional scale and the materials are to have the desired chemical properties. We have developed a new methodology for the high-throughput multiparameter optimization of polymerization reaction conditions in arrays of microreactors. Our strategy is based on the application of nondestructive spectroscopic techniques to measure chemical properties of polymers directly in individual microreactors followed by the multivariate spectral descriptor analysis for rapid determination of the optimal process conditions. We have demonstrated our strategy in the high-throughput multiparameter optimization of process conditions in thin-film melt polymerization reactions performed in 96-microreactor arrays for combinatorial screening of new polymerization catalysts. The combinatorial polymerization system was optimized for the best processing parameters using a set of input variables that included reactant parameters (relative amounts of starting components and catalyst loading) and processing variables (reaction time, reaction temperature, and inert gas flow rate). The measured output parameters were the chemical properties of materials and reproducibility of the material formation in replicate polymerizations in microreactors. Spatially resolved nondestructive evaluation of polymer formation was performed directly in individual microreactors and provided information about the spatial homogeneity of polymers in microreactors. It showed to be another powerful indicator of the reproducible polymerization process on the combinatorial scale. Although the methodology described here was implemented for high-throughput optimization of polymerization conditions, it is more general and can be further implemented for a variety of applications in which optimization of process parameters can be studied in situ or off-line using spectroscopic and other tools.