Hierarchical multiscale model-based design of experiments, catalysts, and reactors for fuel processing

Abstract In this paper a hierarchical multiscale simulation framework is outlined and experimental data injection into this framework is discussed. Specifically, we discuss multiscale model-based design of experiments to optimize the chemical information content of a detailed reaction mechanism in order to improve the fidelity and accuracy of reaction models. Extension of this framework to product (catalyst) design is briefly touched upon. Furthermore, we illustrate the use of such detailed and reduced kinetic models in reactor optimization as an example toward more conventional process design. It is proposed that hierarchical multiscale modeling offers a systematic framework for identification of the important scale(s) and model(s) where one should focus research efforts on. The ammonia decomposition on ruthenium to produce hydrogen and the water-gas shift reactions on platinum for converting syngas to hydrogen serve as illustrative fuel processing examples of various topics. The former is used to illustrate hierarchical multiscale model development and model-based parameter estimation as well as product engineering. The latter is employed to demonstrate model reduction and process optimization. Finally, opportunities for process design and control in portable microchemical devices (lab-on-a chip) for power generation are discussed

SO_<i>x</i> Oxidation Kinetics on Pt(111) and Pd(111): First-Principles Computations Meet Microkinetic Modeling

This work examines the complex nature of SO_<i>x</i> (<i>x</i> = 0–4) interaction and oxidation on Pt(111) and Pd(111) surfaces using density functional theory (DFT) calculations coupled with microkinetic modeling. Thermodynamic and kinetic analyses suggest similar adsorption and oxidation behaviors for SO_<i>x</i> species on both metal surfaces, although the observed greater tendency of Pd to undergo sulfating is borne out by the present results. Selected quantities computed using DFT, when used in a previously developed microkinetic model, are shown to predict SO₂ conversion as a function of temperature in excellent agreement with available experimental data