An experiment planner for performing successive focused grid searches with an automated chemistry workstation

Abstract

Automated chemistry workstations equipped for parallel and adaptive experimentation can provide a significant impact in chemistry research, particularly for exploring search spaces as part of optimization studies. A traditional method of investigating a search space involves generation of a response surface upon examination of a regular grid of points (e.g., as in a full factorial design). Such experimental approaches are compatible with parallel experimentation but are not adaptive in directing the search toward favorable regions of the search space. We have developed an algorithm wherein a succession of grid searches is performed in a search space. The location of the optimal response obtained in one search cycle constitutes the location about which a subsequent more fine-grained search is performed. In this manner, a sequential iterative optimization can be achieved: one cycle is comprised of a set of parallel reactions followed by data evaluation, and multiple cycles occur until one of several user-defined termination criteria is satisfied. In successive cycles, the number of levels on each dimension can be decremented and the range of each dimension can be decreased by a defined “shrinkage” factor. The resulting successive focused grid search (SFGS) affords a breadth-first then in-depth study. We have developed an experimental planner that enables the SFGS algorithm to be implemented on an automated chemistry workstation. Options are available for adjusting the scope of experimentation to conserve material resources (e.g., solvent, reagents, reactants) or to curtail the duration of experimentation. Collectively, the SFGS module enables parallel adaptive experimentation and affords a comprehensive response surface that is fine-grained in the region of optimal response.