Identification of kinetic models of methanol oxidation on silver in the presence of uncertain catalyst behavior |
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Authors: | Marco Quaglio Fabrizio Bezzo Asterios Gavriilidis Enhong Cao Noor Al-Rifai Federico Galvanin |
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Affiliation: | 1. Department of Chemical Engineering, University College London (UCL), London, UK;2. CAPE-Lab (Computer-Aided Process Engineering Laboratory), Department of Industrial Engineering, University of Padova (UNIPD), Padova, Italy |
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Abstract: | Catalytic oxidation of methanol to formaldehyde is an important industrial process due to the value of formaldehyde either as a final product or as a precursor of numerous chemicals. The study of kinetics in this system is hindered by sources of uncertainty that are inherently associated to the nature and state of the catalyst (e.g., uncertain reactivity level, deactivation phenomena), the measurement system and the structure of the kinetic model equations. In this work, a simplified kinetic model is identified from data collected from continuous flow microreactor systems where catalysts with assorted levels of reactivity are employed. Tailored model-based data mining methods are proposed and applied for the effective estimation of the kinetic parameters and for identifying robust experimental conditions to be exploited for the kinetic characterization of catalysts with different reactivity, whose kinetic behavior is yet to be investigated. |
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Keywords: | data mining information parameter estimation reactivity uncertainty |
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