Micromixing selectivity

Nagaki, A., et al., Control of extremely fast competitive consecutive reactions using micromixing. Selective Friedel-Crafts aminoalkylation. Journal of the American Chemical Society, 2005, 127 11666-11675. 

The reactor has been successfully used in the case of forced precipitation of copper and calcium oxalates (Jongen etal., 1996 Vacassy etal., 1998 Donnet etal., 1999), calcium carbonate (Vacassy etal., 1998) and mixed yttrium-barium oxalates (Jongen etal., 1999). This process is also well adapted for studying the effects of the mixing conditions on the chemical selectivity in precipitation (Donnet etal., 2000). When using forced precipitation, the mixing step is of key importance (Schenk etal., 2001), since it affects the initial supersaturation level and hence the nucleation kinetics. A typical micromixer is shown in Figure 8.35. 

In order to implement the PDF equations into a LES context, a filtered version of the PDF equation is required, usually denoted as filtered density function (FDF). Although the LES filtering operation implies that SGS modeling has to be taken into account in order to capture micromixing effects, the reaction term remains closed in the FDF formulation. Van Vliet et al. (2001) showed that the sensitivity to the Damkohler number of the yield of competitive parallel reactions in isotropic homogeneous turbulence is qualitatively well predicted by FDF/LES. They applied the method for calculating the selectivity for a set of competing reactions in a tubular reactor at Re = 4,000. 

Micromixing may also have a major impact upon the yield and selectivity of complex reaction networks. Consider, for example, the following parallel reaction network, where both a desired product (D) and an undesired product (U) may be formed ... 

If both reactions are first order (a = j8 = 1), then micromixing is irrelevant yield, selectivity, and fractional conversion depend solely on the RTD. If, however, either a or /3 is not equal to 1, then the degree of micromixing can have a significant impact upon performance, as illustrated in the following example. 

Multi-environment presumed PDF models can also be easily extended to treat cases with more than two feed streams. For example, a four-environment model for a flow with three feed streams is shown in Fig. 5.24. For this flow, the mixture-fraction vector will have two components, 2 and 22- The micromixing functions should thus be selected to agree with the variance transport equations for both components. However, in comparison with multi-variable presumed PDF methods for the mixture-fraction vector (see Section 5.3), the implementation of multi-environment presumed PDF models in CFD calculations of chemical reactors with multiple feed streams is much simpler. 

Figure 5.25 The impact of choice of micromixer on selectivity when varying the phenol/hydroxybenzylalcohol molar ratio (by courtesy of Wiley-VCH Verlag GmbH) [57],...

In this section, we present examples to illustrate the usefulness of multi-mode homogeneous reactor models in predicting micromixing effects on yield and selectivity, reactor runaway, etc. 

Competitive- Consecutive Reaction in a CSTR Micromixing Effects on Selectivity... 

For the first two cases Da << 1 (slow reactions) and Da >> 1 (very fast reactions) adequate closure models are available in many commercial CFD codes. For the third case, where the time scale for chemical conversion approximately equals the time scale for turbulent micromixing, moment methods are inappropriate and other methods should be used. In this situation the reactor performance may be significantly affected by mixing efficiency. Here the engineer is faced with the difficult problem of predicting the overall conversion and/or selectivity of the chemical process. In the last three decades this problem has received considerable attention in three scientific areas, namely, chemical reaction engineering, fluid mechanics and combustion, and various approaches have been followed. 

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