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. 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. Finally, opportunities for process design and control in portable microchemical devices (lab-on-a chip) are discussed.
['D. G. Vlachos', 'A. B. Mhadeshwar', 'Niket S. Kaisare']
Hierarchical multiscale model-based design of experiments, catalysts, and reactors for fuel processing