Exchange model, selection

The data in fig. 5 were simulated using the multi-site ion exchange model of Barrer and Klinowski (92). The model essentially consists in assigning intrinsic selectivity coefficients to the... 

A. I. Kalinitchev, in Chapter 4, deals with the kinetics of ion exchange in selective systems. In particular he uses the kinetic model developed in his research to show that phenomenological regularities and criteria describing intraparticle diffusion kinetics for conventional ion exchange are not applicable to selective ion-exchange systems. 

In another study Sellergren and Shea [78] modelled the chromatographic behaviour of a solute, PA, on imprinted and non-imprinted polymers using a simple cation-exchange model, and were able to describe the behaviour as a function of mobile phase pH. Moreover, the model they proposed was sufficient to explain the differences in selectivity between the two polymers. 

A number of other studies using uncharged templates or acids imprinted using VPY as functional monomer show pH dependent selectivities that can be rationalised considering this type of ion exchange model [144]. 

It should also be recognized that collecting more data may not necessarily alleviate model selection biases. Newly collected data may not be fully exchangeable with the current data set (an observation that has profound implications for model validation) and so model development based on more data may not lead to the same model or the same conclusions. Lastly, a model based on data can never be proven. No amount of data can prove a model is correct, no matter how simple. A model can only be disproved. 

Wave motion similar to that examined in the previous section occurs in other applications of fixed-bed technology. Important among these are processes involving ion exchange or selective adsorption. While these are for the most part separation processes and may or may not include chemical reactions, the analysis is too closely related to what we have been discussing to allow it to pass by now. The nature of the equilibrium between fiuid and solid phases plays a more direct and obvious role than in pseudo-homogeneous reactor models, and provides a convenient means for classification. 

As a remark, the above model can be adjusted to reflect different simations (i) where only the most fouled exchangers are selected to clean (ii) where time variant margin is estimated instead of average margin and (iii) other significant costs are introduced. 

Removing the heat of reaction necessitates an internal heat exchanger. This exchanger will also help to limit the bubble diameter. Take vertical tubes of 0.06 m outer diameter on a 0.14-m triangular pitch. This limits the effective diameter of the bubbles to 0.1 m. Note that this is a very crude way of determining the (average) bubble diameter, which is the main variable in the Kunii and Levenspiel model. Select the superficial velocity of the feed to be 1800 m/h. Calculate the mass transfer coefficients from (13.5.3-4) and (13.5.3-5) and use (13.5.3-13) to calculate the bed height. 

Many models have been proposed for adsorption and ion exchange equilibria. The most important factor in selecting a model from an engineering standpoint is to have an accurate mathematical description over the entire range of process conditions. It is usually fairly easy to obtain correcl capacities at selected points, but isotherm shape over the entire range is often a critical concern for a regenerable process. 

With respect to selecting measurements, emphasis should include measurements within the equipment such as tower internal temperatures and compositions, internal reac tor conditions, and intermediate exchanger temperatures in multipass exchangers. Trace component compositions provide particular insight into distillation-column performance. Those components that fall between the heavy and light keys and distribute in the products can usually be described by a variety of models and parameter estimates They provide little insight into the column performance. 

Caraculacu et al. [48] also quantitatively determined allylic chlorines in PVC by isotopic exchange with SO Cl2. The selective exchange of chlorine in the polymer was verified by experiments with model compounds. The number of allylic chlorines in PVC was found to be between 0.12 and 0.16 for 100 monomer units. 

---