Tracking Chemical Kinetics in High-Throughput Systems

Combinatorial chemistry and high‐throughput experimentation (HTE) have revolutionized the pharmaceutical industry—but can chemists truly repeat this success in the fields of catalysis and materials science? We propose to bridge the traditional “discovery” and “optimization” stages in HTE by enabling parallel kinetic analysis of an array of chemical reactions. We present here the theoretical basis to extract concentration profiles from reaction arrays and derive the optimal criteria to follow (pseudo)first‐order reactions in time in parallel systems. We use the information vector f and introduce in this context the information gain ratio, χr, to quantify the amount of useful information that can be obtained by measuring the extent of a specified reaction r in the array at any given time. Our method is general and independent of the analysis technique, but it is more effective if the analysis is performed on‐line. The feasibility of this new approach is demonstrated in the fast kinetic analysis of the carbon–sulfur coupling between 3‐chlorophenylhydrazonopropane dinitrile and β‐mercaptoethanol. The theory agrees well with the results obtained from 31 repeated CS coupling experiments. Why are chemists having problems reproducing the huge pharmaceutical success of combinatorial chemistry in the fields of catalysis and materials science? One reason is that the traditional separation between the “discovery” and “optimization” stages does not suit the search for new catalysts. We try and bridge this gap through parallel kinetic analysis of an array of chemical reactions (see diagram). We evaluate methods to extract concentration profiles from reaction arrays and show how to measure the future information content from each single reaction.