Kinetic Analysis and Reactor Design of Ethanol Steam Reforming

A set of kinetic tests for ethanol steam reforming have been performed and were used as basis for kinetic modelling of the reaction. We performed 25 tests varying temperature, space velocity and water/ethanol ratio according to a composite design of experiments. The results were quantitatively used to understand the parametric dependence of conversion and selectivity on the selected variables, including statistical analysis. Microkinetic modelling followed, specifically focusing on the steps that predict by-products formation. At difference with literature we also interpreted coke accumulation over catalyst surface. Literature data were also modelled to check for consistency and versatility of the proposed kinetic scheme. 1. Scope An experimental kinetic investigation has been carried out for ethanol steam reforming (ESR). The selected catalyst was a 9 wt% K2O-10 wt% Ni/ZrO2 sample prepared by flame pyrolysis, which revealed particularly active and stable for this application based on previous investigations of the group. Ethanol conversion, selectivity to the main possible byproducts (methane, ethylene and acetaldehyde), hydrogen productivity and the CO/CO2 ratio, as a measure of the contribution of the water gas shift reaction, were correlated to the experimental variables chosen. They were temperature, water/ethanol ratio and space velocity explored in the variable space by means of a central composite experimental design. The parametric dependence of the reaction outcomes helped the qualitative assessment of the best operating conditions and suggested hypotheses on the reaction mechanism. A more quantitative parametric analysis was carried out by multivariate analysis. Particularly dramatic experimental conditions have been adopted in order to highlight the formation and further evolution of possibly critical intermediates, such as ethylene and acetaldehyde. Indeed, to keep ethanol and intermediates conversion below 100% at least at 550\ub0C to guarantee coke-free operation, the space velocity and feed dilution were increased. An extended microkinetic model has been proposed for the ethanol steam reforming reaction that includes kinetic steps for the formation of important byproducts such as ethylene, acetaldehyde and coke. The model, initially drawn on our own experimental data, was also validated against literature data collected over a different catalytic system and without the presence of the selected byproducts. 2. Results and discussion The catalyst was tested under the following experimental conditions [1]: Min Max T (\ub0C) 550 650 Catalyst (mg) 26 132 EtOH : H2O (mol/mol) 1 : 5 1 : 3 GHSV (h-1) 25000 125000 An increase of temperature did not adequately improved H2 selectivity, whereas the water/ethanol ratio was an effective parameter to push forward H2 productivity. The reforming reactions of ethanol and of acetaldehyde/ethylene byproducts were dependent on the three parameters (kinetically controlled), whereas the CO/CO2 ratio was substantially independent on the space velocity, indicating that the water gas shift reaction reached a quasi-equilibrium value. The data were elaborated by setting up a Matlab script for data regression. A Plug-flow reactor model was implemented, neglecting radial dispersion and back mixing. Isothermal operation was assumed and checked experimentally, due to the very low amount of catalyst, diluted in SiC. The same model was also implemented in the Aspen Plus\uf0d2 process simulator, obtaining comparable results. The proposed micrikinetic model, sketched in Figure 1, gave very straightforward predictions of catalyst performance for the literature data: in this case the lump sum of all the square residues (calculated vs. tabulated mol fractions) was 2.88 x 10-2 over a dataset of 408 points [2,3]. For our own kinetic data, the model optimally predicted the conversion of ethanol and the evolution of the main byproducts, which include ethylene and acetaldehyde (Fig. 2). The evolution of coke was interpreted less satisfactorily because of a missing step for coke gasification. Rate-limiting steps have been identified together with very rapid reaction steps, which can be considered to be substantially equilibrated. Figure 1: Microkinetic model proposed for ethanol steam reforming. Red routes add paths to a literature model to account for the formation of interesting intermediates [3]. Figure 2: Accurate interpolation of the kinetic steady-state reached by the still non-equilibrated carbon-containing species deriving from ethanol reforming (line: best non-linear fit, points: lab data) [1]. M = methane. 3. Conclusions A parametric study and kinetic testing for ethanol steam reforming has been carried out on a K-promoted Ni/ZrO2 catalyst prepared by flame pyrolysis. Ethanol conversion, H2 productivity and selectivity to different byproducts were checked depending on temperature, space velocity and the water/ethanol feeding ratio. Very stressing conditions allowed to highlight the formation of possibly critical byproducts, such as ethylene and acetaldehyde, which are not usually accounted for in the literature. The water/ethanol ratio revealed a particularly sensitive parameter. In general, ethanol and C2 byproducts conversion was improved by increasing temperature, contact time and water/ethanol ratio. Methane was a minor byproduct in most cases, but showed lower dependence on most parameters. An original microkinetic reaction mechanism was drawn to interpret these data. This model allows the prediction of the formation rate of possibly critical byproducts, especially acetaldehyde, ethylene and coke, which may contribute to catalyst deactivation. In addition, it can furnish interesting information on the reaction pathways. The model proved sufficiently robust to keep its coherence with simpler parent mechanisms, while flexible enough to account for the presence of additional chemicals. References 1. Compagnoni, M.; Tripodi, A.; Rossetti, I. Appl. Catal. B: Environ. 2017, 203, 899\u2013909. 2. Tripodi, A.; Compagnoni, M.; Rossetti, I. ChemCatChem 2016, 8, 3804\u20133813. 3. Llera, I.; Mas, V.; Bergamini, M.L.; Laborde, M.; Amadeo, N. Chem. Eng. Sci. 2012, 71, 356\u2013366