Confounded reactors

Determine physical property and kinetic data from the literature or laboratory studies. 

Combine these data with estimates of the transport parameters to model the desired full-scale plant. 

Scale down the model to design a pilot plant that is scalable upward and that will address the most significant uncertainties in the model of the full-scale facility. 

Operate the pilot plant to determine the uncertain parameters. These will usually involve mixing and heat transfer, not basic kinetics. 

Revise the model and build the full-scale plant. 

The general approach of Eqnation 7.1 is applicable to any type of system  

Condnct kinetic experiments and measure some response of the system. Call this experiment.  

Pick a model for the system and assume values for the model s parameters. Solve the model to predict the response. Call this model.  

There is no reqnirement that the model represent a simple reactor snch as a CSTR or isothermal PER. If necessary, the model can represent a nonisothermal PER with variable physical properties. It can be one of the distributed parameter models in Chapters 8 or 9. The model parameters can inclnde the kinetic parameters in Equations 

6 together with unknown transport properties such as a heat transfer coefficient. However, the simpler the better, and the extraction of rate data can be difficult if the model is confounded by heat and mass transfer effects. 

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A relatively simple example of a confounded reactor is a nonisothermal batch reactor where the assumption of perfect mixing is reasonable but the temperature varies with time or axial position. The experimental data are fit to a model using Equation (7.8), but the model now requires a heat balance to be solved simultaneously with the component balances. For a batch reactor. 

Confounded reactors are likely to stay confounded. Data correlations can produce excellent fits and can be useful for predicting the response of the particular system on which the measurements were made to modest changes in operating conditions. They are unlikely to produce any fundamental information regarding the reaction rate, and have very limited utility in scaleup calculations. 

The 1.53-order reaction of Example 7.5 is not elementary and could involve shortlived intermediates, but it was treated as a single reaction. We turn now to the problem of fitting kinetic data to multiple reactions. The multiple reactions listed in Section 2.1 are consecutive, competitive, independent, and reversible. Of these, the consecutive and competitive types, and combinations of them, pose special problems with respect to kinetic studies. They will be discussed in the context of integral reactors, although the concepts are also applicable to the CSTRs of Section 7.1.1 and to the confounded reactors of Section 7.1.6. 

Multiphase Reactors. The overwhelming majority of industrial reactors are multiphase reactors. Some important reactor configurations are illustrated in Figures 3 and 4. The names presented are often employed, but are not the only ones used. The presence of more than one phase, whether or not it is flowing, confounds analyses of reactors and increases the multiplicity of reactor configurations. Gases, Hquids, and soHds each flow in characteristic fashions, either dispersed in other phases or separately. Flow patterns in these reactors are complex and phases rarely exhibit idealized plug-flow or weU-stirred flow behavior. 

Traditionally, CVD reaction data have been reported in terms of growth rates and their dependence on temperature. The data are often confounded by mass-transfer effects and are not suitable for reactor analysis and design. Moreover, CVD reaction data provide little insight, if any, into impurity incorporation pathways. Therefore, the replacement of traditional macroscopic deposition studies with detailed mechanistic investigations of CVD reactions is an area of considerable interest. A recent, excellent review of CVD mechanistic studies, particularly of Si CVD, is available (98), and the present discussion will be limited to highlighting mechanisms of Si CVD and of GaAs deposition by MOVCD as characteristic examples of the combined gas-phase and surface reaction mechanisms underlying CVD. 

The aggregation of cells in suspension culture leads to a heterogeneous population that confound the analysis and operations of the reactor types mentioned above in many cases. For non-growth associated products, immobilization of cells provides a... 

Sometimes in a factorial experiment we have a double restriction imposed on the system. For example, in a 2 experiment (5 factors all at 2 levels, requiring a total of 32 runs) we may have 4 reactors which may be different. Accordingly we conform d in 4 blocks of 8, there being 8 runs on each of the 4 reactors. However, our batches of raw material may not be large enough to carry out the whole experiment. We then need to confoimd the experiment in an additional way. The problem is soluble if we make it the inverse of the first type of confounding. Thus, if the first confounding is in 4 blocks of 8 then the second must be in 8 blocks of 4. There is the further restriction that no interaction confounded in the second set must occur in the first set, and vice versa. 

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