Bulk properties reforming

The final step in the integrated model before fractionation is the delumping of products and prediction of bulk properties. Since our lumping system is quite broad, we can just calculate key properties of the reformer effluent as combination of the individual projjerties of the lumps. 

Another method is to try and estimate the composition of the reactors based only on bulk property information. This bulk property information typically refers to routinely measured properties such density, distillation curves, etc. Klein and co-workers [29] have used a much more sophisticated version of this approach to probabilistically sample candidate molecules and generate a very large list of molecules whose combined properties match the measured bulk properties. Hu et al. [24] use a probabibty distribution method to estimate to the PN A compositions for their approach towards refinery reactor modeling. The approach we describe is similar, but much simpler to use since it is targeted only for reformer feeds. 

Figure 5.54 shows the Feed Data tab from the Reformer sub-model. The Feed Type is a basic set of relationships and initial values for the all kinetic lumps in the reactor model. Aspen HYSYS uses bulk property information such as density, distillation curves and total PNA content in conjunction with the feed type to predict the composition of feed lumps to the model. The Default type is sufficient for hght-to-heavy naphtha. However, there is no guarantee that a particular feed type represents the actual feed accurately. Aspen HYSYS will attempt to manipulate the feed composition to satisfy bulk property measures given. In general, we advise users to develop a few sets of compositional analysis to verify the kinetics lumps calculated by Aspen HYSYS. We discuss a process to verify these lumps later. 

In the previous section, we built and solved the reformer model using bulk property and total PNA information only. This approach works reasonably when the actual feedstock is quite similar to the Default or selected feed type. In actual refinery operation, the feed type may change quickly or may not have been analyzed for feed type information. In this section, we discuss an approach to integrate measured molecular composition analysis with the feed type to improve modeling results. This method has shown significant improvement in model predictions, especially in the petrochemical reformers where accurate predictions of aromatic content are significant... 

Water-in-oil microemulsions (w/o-MEs), also known as reverse micelles, provide what appears to be a very unique and well-suited medium for solubilizing proteins, amino acids, and other biological molecules in a nonpolar medium. The medium consists of small aqueous-polar nanodroplets dispersed in an apolar bulk phase by surfactants (Fig. 1). Moreover, the droplet size is on the same order of magnitude as the encapsulated enzyme molecules. Typically, the medium is quite dynamic, with droplets spontaneously coalescing, exchanging materials, and reforming on the order of microseconds. Such small droplets yield a large amount of interfacial area. For many surfactants, the size of the dispersed aqueous nanodroplets is directly proportional to the water-surfactant mole ratio, also known as w. Several reviews have been written which provide more detailed discussion of the physical properties of microemulsions [1-3]. 

Friedrich M, Teschner D, Knop-Gericke A, Armbriister M. Influence of bulk composition of the intermetallic compound ZnPd on surface composition and methanol steam reforming properties. J Catal. 2012 285 41-47. 

Water is both a donor and acceptor of hydrogen bonds. Consequently, in bulk solvent, water molecules are extensively hydrogen bonded to each other. These are relatively weak bonds ( 5 kcal/mol) and, at physiological temperature, are rapidly broken and reformed. However, the hydrogen-bonding network affects many of the properties of water. 

Under catalytic reaction conditions, one should not necessarily expect species to proceed to the thermodynamic final state. An additional complication comes from the fact that the redox properties of catalytically active ceria and of ceria-zirconia mixed oxides appear to be quite different from the bulk thermodynamic values for ceria [37,38]. For example, ceria films calcined above 1270 K no longer promote the WGS [22] or steam-reforming reactions [20] and are much more difficult to reduce upon heating in vacuum [39]. These observations appear to be explained by calorimetric studies, which have shown that the heat of reoxidation for reduced Pd/ceria and Pd/ceria-zirconia catalysts is much lower than bulk thermodynamics would suggest [38]. Therefore, bulk thermodynamic information may not be entirely relevant for describing the nature of sulfur-containing species on catalytically active materials. 

The use of oxide-type perovskites as dry reforming catalysts will be dealt with extensively in Volume II of this book. In this chapter, we report one example of such catalyst in order to highlight the potentiahty of the nanocasting preparation method as a way to control bulk and smface properties of perovskite-derived catalysts. 

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