Research Methodology

    The scale gap between observable reaction rates and catalytic surface reactions on the nanoscale can be bridged through a hybrid experimental-theoretical approach.

    An iterative cycle of experimental catalyst characterization and testing combined with density-functional theory (DFT) calculations of surface species provides information for the development of reaction mechanisms. Experimental information establishes the basis for the selection of models and the level of theory for DFT calculations and then, in turn, results of the DFT calculations allow to deconvolute and better interpret experimental data. A combination of kinetic testing, infrared spectroscopy, adsorption measurements and temperature programmed reaction with DFT calculations proved to be particularly useful in understanding surface chemistry [2, 5, 6, 8, 9, 10, 11, 12].

    Experimental and theoretical results on the modes of adsorption, energetics and reactivity of surface species can be consolidated into a traditional kinetic model for the description of observable reaction rates [2, 6]. For more detailed studies on the connection between nano-scale chemistry and macroscopic properties, results of DFT calculations can be combined with Monte Carlo (MC) simulations. For example, MC simulations were useful in evaluating effects of lateral interactions on co-adsorption of surface species [11, 12]. Specially developed MC simulations were also useful in merging into a single model dramatically different reactivity time scales of spectator and active species [10].

    A combination of catalyst characterization and testing with DFT calculations and kinetic modeling provides direction for catalyst and process development. For example, favorable reaction conditions [2, 3, 4] or critical steps in the reaction mechanism can be identified [1, 6, 7, 8]. In addition, the reactivity of surface formulations that are difficult to study experimentally can be evaluated computationally [5]. This approach can be generalized and extended to computational screening of various metal and metal oxide materials for catalytic transformations of light hydrocarbons, and it should provide the basis for establishing structure-activity correlations with the ultimate goal of rational catalyst design.

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Last updated on 21 Dec 2011.

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