A C1 microkinetic model for methane conversion to syngas on Rh/Al2O3

Authors

  • Matteo Maestri,

    1. Dept. of Chemical Engineering and Center for Catalytic Science and Technology (CCST), University of Delaware, Newark, DE, 19716
    2. Laboratory of Catalysis and Catalytic Processes, Dipartimento di Energia, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
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  • Dionisios G. Vlachos,

    Corresponding author
    1. Dept. of Chemical Engineering and Center for Catalytic Science and Technology (CCST), University of Delaware, Newark, DE, 19716
    • Dept. of Chemical Engineering and Center for Catalytic Science and Technology (CCST), University of Delaware, Newark, DE, 19716
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  • Alessandra Beretta,

    1. Laboratory of Catalysis and Catalytic Processes, Dipartimento di Energia, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
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  • Gianpiero Groppi,

    1. Laboratory of Catalysis and Catalytic Processes, Dipartimento di Energia, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
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  • Enrico Tronconi

    1. Laboratory of Catalysis and Catalytic Processes, Dipartimento di Energia, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
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Abstract

A microkinetic model capable of describing multiple processes related to the conversion of natural gas to syngas and hydrogen on Rh is derived. The parameters of microkinetic models are subject to (intrinsic) uncertainty arising from estimation. It is shown that intrinsic uncertainty could markedly affect even qualitative model predictions (e.g., the rate-determining step). In order to render kinetic models predictive, we propose a hierarchical, data-driven methodology, where microkinetic model analysis is combined with a comprehensive, kinetically relevant set of nearly isothermal experimental data. The new, thermodynamically consistent model is capable of predicting several processes, including methane steam and dry reforming, catalytic partial oxidation, H2 and CO rich combustion, water-gas shift and its reverse at different temperatures, space velocities, compositions and reactant dilutions, using the measured Rh dispersion as an input. Comparison with other microkinetic models is undertaken. Finally, an uncertainty analysis assesses the effect of intrinsic uncertainty and catalyst heterogeneity on the overall model predictions. © 2009 American Institute of Chemical Engineers AIChE J, 2009

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