Multiscale Model and Informatics-Based Optimal Design of Experiments : Application to the Catalytic Decomposition of Ammonia on Ruthenium

Fundamental multiscale models are increasingly being used to describe complex systems. Microkinetic models, which consider a detailed surface reaction mechanism containing all relevant reactions, are a prototypical multiscale model example. The computational effort in calculating all parameters of a multiscale model for real systems from first principles is prohibitive, and parameter uncertainty still limits full quantitative capabilities of these models. This motivates the development of rational model-based techniques in order to refine uncertain parameters and assess the global (in the entire experimental parameter space) model robustness. Herein we describe physics-aided methods (sensitivity, partial equilibrium, and most abundant reactive intermediate analyses) and statistics-based methods (A, D, and E optimal designs) for the design of experiments. While our methods are fairly general, we demonstrate them for the catalytic decomposition of ammonia on ruthenium to produce hydrogen. A global Monte Car...