386268 Quantitative Analysis of Light-Off Profiles for Kinetic Parameters

Monday, November 17, 2014: 3:15 PM
303 (Hilton Atlanta)
Daniel Coller, Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA and Susannah L. Scott, Departments of Chemical Engineering and Chemistry, University of California, Santa Barbara, Santa Barbara, CA

Kinetic parameters for heterogeneous reactions, such as the activation energy, Ea, the Arrhenius pre-exponential factor, A, and the reaction orders for each reactant/product, are typically obtained from a series of experimental rate measurements, each made under isothermal conditions. The accuracy of the resulting activation parameters can be low (although it is often unacknowledged to be so), due to the small number of measurements, the limited temperature range used, and the assumption of differential (i.e., gradient-less) reactor conditions.

     Although light-off profiles are quick and easy to generate, and may contain high quality data over conversions ranging from negligible to full, such data are rarely exploited quantitatively. We considered whether curve-fitting non-isothermal data could be used to generate faster and more accurate kinetic information about both the rate law and the activation parameters. Simulation of light-off profiles shows that different rate laws give rise to distinctive profile shapes, influenced primarily by the reaction order of the limiting species.

     Light-off profiles for CO oxidation by O2 over PdO supported on γ-alumina were generated with different residence times and inlet concentration ratios. Our simulated light-off profiles correctly predict the shape and position of each experimental non-isothermal dataset. By fitting the kinetic equations to the data, values for the activation parameters and reaction orders were obtained that are identical to those obtained from traditional isothermal measurements; however, the experimental uncertainty and time required to obtain them were greatly reduced. This method can be used to screen many catalysts rapidly to compare their kinetic behavior and to look for irregularities that may signal transport limitations, a change in rate-limiting step, or a change in surface composition, making it potentially useful as a tool to complement high-throughput catalyst synthesis.


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