An intuitive approach for optimal design of experiments for Langmuir-Hinshelwood reaction kinetics

A proper experimental design is of central importance for carrying out an efficient parameter estimation of heterogeneous reaction kinetics. The outcome of parameter estimation impacts the design, analysis, and optimization of chemical reactors. Commonly, practitioners conduct experiments based on heuristic or ad hoc designs, which can induce statistical bias, excessive amplification of experimental errors, and unnecessary costs. With this in mind, optimal design of experiments (DOE) is an alternative for establishing experimental configurations that are both statistically and economically efficient. Optimal DOE dates back at least 100 years, but its extensive use in chemical kinetics is still limited. One possible reason for this limitation is that optimal DOE relies on rigorous statistical and mathematical methods, which are generally intractable for many practitioners. The aim of this work is to explore optimal DOE for Langmuir-Hinshelwood kinetics from a more intuitive than rigorous perspective. The motivation is to promote the use of systematic DOE techniques that are accessible to practitioners with an elementary background in calculus and algebra.