Transient experiments, rate coefficients

Table I lists the values of the rate coefficients used to simulate the transient response experiments shown in Figs. 3 through 8. These values were obtained in the following manner (29). Starting from a set of initial guesses, the values of k were varied systematically to obtain a fit between the predicted product responses and those obtained from experiments in which H2 was added suddenly to a flow of NO. These experiments while not described here were identical to that presented in Fig. 9, with the exception that only l NO was used. Because of the large number of parameters in the model, only a rough agreement could be achieved between experiment and theory even after 500 iterations of the optimization routine (30). The parameter values obtained at this point were now used to calculate the responses expected during the reduction of adsorbed NO. These computations produced responses similar to those observed experimentally (i.e., Fig. 3) but the appearance of the product peaks in time did not coincide with those observed. To correct for this, the values of kg, ky, and kg were adjusted in an empirical manner.

Table I. Rate Coefficients Used to Simulate the Transient Response Experiments...

Kinetic rate coefficients have been determined for the reduction of NO by CO in absence and presence of O2 via regression of transient experiments at automotive cold-start conditions over a commercial Pt/Rh/Ce02/y-Al203 catalyst. The kinetic model quantifies storage and release of O2 and NO in ceria during lean and rich half-cycles. 

This paper provides kinetic rate coefficients of a transient elementary step model for NO reduction by CO in the absence and presence of O2 over a commercial three-way catalyst. This model has been obtained by combining previously published results fixrm CO oxidation [24] and NO reduction [25] experiments. The model is able to adequately predict NO reduction experiments at cold-start temperatures under both rich and lean conditions. Storage effects of ceria and noble metal-ceria interactions are explicitly taken into account. Furthermore, the model predicts surface coverages on the various active locations of the catalyst. 

Carbon Dioxide Transport. Measuring the permeation of carbon dioxide occurs far less often than measuring the permeation of oxygen or water. A variety of methods ate used however, the simplest method uses the Permatran-C instmment (Modem Controls, Inc.). In this method, air is circulated past a test film in a loop that includes an infrared detector. Carbon dioxide is appHed to the other side of the film. AH the carbon dioxide that permeates through the film is captured in the loop. As the experiment progresses, the carbon dioxide concentration increases. First, there is a transient period before the steady-state rate is achieved. The steady-state rate is achieved when the concentration of carbon dioxide increases at a constant rate. This rate is used to calculate the permeabiUty. Figure 18 shows how the diffusion coefficient can be deterrnined in this type of experiment. The time lag is substituted into equation 21. The solubiUty coefficient can be calculated with equation 2. 

Errors and confusion in modelling arise because the complex set of coupled, nonlinear, partial differential equations are not usually an exact representation of the physical system. As examples, first consider the input parameters, such as chemical rate constants or diffusion coefficients. These input quantities, used as submodels in the detailed model, must be derived from more fundamental theories, models or experiments. They are usually not known to any appreciable accuracy and often their values are simply guesses. Or consider the geometry used in a calculation. It is often one or two dimensions less than needed to completely describe the real system. Multidimensional effects which may be important are either crudely approximated or ignored. This lack of exact correspondence between the model adopted and the actual physical system constitutes the basic problem of detailed modelling. This problem, which must be overcome in order to accurately model transient combustion systems, can be analyzed in terms of the multiple time scales, multiple space scales, geometric complexity, and physical complexity of the systems to be modelled. 

The diffusion coefficient can be determined from the transient portion of a complete permeation experiment. Figure 2 shows how the transport rate or detector response varies with time during a complete experiment. At the beginning of an experiment, t = 0, a clean film is exposed to the permeant on the upstream side. 

Cumene is cracked in a recycle reactor over commercial H-ZSM5 extrudates. A Thiele modulus approach is used to determine the diffusion coefficient and the intrinsic rate constant. The results are compared to those obtained from pulse experiments. A linear model for diffusion, adsorption and reaction rate is applied for reactants and products. In contrast to literature it is argued that if the Thiele modulus is greater than five, the system becomes over parameterised. If additionally adsorption dynamics are negligible, only one lumped parameter can be extracted, which is the apparent reaction constant found from steady state experiments. The pulse experiment of cumene is strongly diffusion limited showing no adsorption dynamics of cumene. However, benzene adsorbed strongly on the zeolite and could be used to extract transient model parameters which are compared to steady state parameters. 

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