Effective kinetics modeling

To estabhsh an effective kinetic model, every reasonable mechanism based upon previous experimental studies is analyzed. Discrimination between each of them is then performed by comparison of their fit with the experimental kinetic data. Importantly, this mathematical treatment can be used to deconvolute the initiation rate constant of the active catalyst from the actual rate constant of the catalytic cycle, thereby alleviating the need for parameters outside the actual regime of the catalytic reaction. 

The early kinetic models for copolymerization, Mayo s terminal mechanism (41) and Alfrey s penultimate model (42), did not adequately predict the behavior of SAN systems. Copolymerizations in DMF and toluene indicated that both penultimate and antepenultimate effects had to be considered (43,44). The resulting reactivity model is somewhat compHcated, since there are eight reactivity ratios to consider. 

The first quantitative model, which appeared in 1971, also accounted for possible charge-transfer complex formation (45). Deviation from the terminal model for bulk polymerization was shown to be due to antepenultimate effects (46). Mote recent work with numerical computation and C-nmr spectroscopy data on SAN sequence distributions indicates that the penultimate model is the most appropriate for bulk SAN copolymerization (47,48). A kinetic model for azeotropic SAN copolymerization in toluene has been developed that successfully predicts conversion, rate, and average molecular weight for conversions up to 50% (49). 

The coupling of supercritical fluid extraction (SEE) with gas chromatography (SEE-GC) provides an excellent example of the application of multidimensional chromatography principles to a sample preparation method. In SEE, the analytical matrix is packed into an extraction vessel and a supercritical fluid, usually carbon dioxide, is passed through it. The analyte matrix may be viewed as the stationary phase, while the supercritical fluid can be viewed as the mobile phase. In order to obtain an effective extraction, the solubility of the analyte in the supercritical fluid mobile phase must be considered, along with its affinity to the matrix stationary phase. The effluent from the extraction is then collected and transferred to a gas chromatograph. In his comprehensive text, Taylor provides an excellent description of the principles and applications of SEE (44), while Pawliszyn presents a description of the supercritical fluid as the mobile phase in his development of a kinetic model for the extraction process (45). 

Figure 9.2. Effect of catalyst potential Uwr, work function 0 and corresponding Na coverage on the rate of C2H4 oxidation on Pt/p"-Al203.1 The dashed line is from the kinetic model discussed in ref. 1. pO2=5.0 kPa, pC2H4=2-1 x 1 O 2 kPa, T=291°C, kad = 12.5 s 1. Reprinted with permission from Academic Press.

Figure 9.8. Effect of catalyst potential Uwr on the apparent activation energy and on the temperature (inset) at which the transition occurs from a high ( ) to a low (O) E value. The dashed lines and predicted asymptotic Ej, E2, E3 activation energy values are from the kinetic model discussed in ref. 11. Conditions p02=5.8 kPa, pCo=3-5 kPa.11 Reprinted with permission from Academic Press.

Doubling the separation of polar molecules reduces the strength of the interaction by a factor of 26 = 64, and so dipole-dipole interactions between rotating molecules have a significant effect only when the molecules are very close. We can now start to understand why the kinetic model accounts for the properties of gases so well gas molecules rotate and are far apart for most of the time, so any intermole-cular interactions between them are very weak. Equation 4 also describes attractions between rotating molecules in a liquid. However, in the liquid phase, molecules are closer than in the gas phase and therefore the dipole-dipole interactions are much stronger. 

This section is divided into three parts. The first is a comparison between the experimental data reported by Wisseroth (].)for semibatch polymerization and the calculations of the kinetic model GASPP. The comparisons are largely graphical, with data shown as point symbols and model calculations as solid curves. The second part is a comparison between some semibatch reactor results and the calculations of the continuous model C0NGAS. Finally, the third part discusses the effects of certain important process variables on catalyst yields and production rates, based on the models. 

Reactor Variable Study. Assuming that the kinetic models are valid, we have a means to rapidly explore the effects of making certain changes in the catalyst or in the operating conditions. Fortunately, Wisseroth published the results for two runs at 100 C and two more runs at 20 atm in his Table 3 (1 ). 

I will assume that these kinetic models correctly account for temperature changes. More data are needed to verify this. The temperature effect in GASPP is practically the same as that claimed by Wisseroth in a recent letter (10). 

This chapter is restricted to homogeneous, single-phase reactions, but the restriction can sometimes be relaxed. The formation of a second phase as a consequence of an irreversible reaction will not affect the kinetics, except for a possible density change. If the second phase is solid or liquid, the density change will be moderate. If the new phase is a gas, its formation can have a major effect. Specialized models are needed. Two-phase ffows of air-water and steam-water have been extensively studied, but few data are available for chemically reactive systems. 

Minimizing the cycle time in filament wound composites can be critical to the economic success of the process. The process parameters that influence the cycle time are winding speed, molding temperature and polymer formulation. To optimize the process, a finite element analysis (FEA) was used to characterize the effect of each process parameter on the cycle time. The FEA simultaneously solved equations of mass and energy which were coupled through the temperature and conversion dependent reaction rate. The rate expression accounting for polymer cure rate was derived from a mechanistic kinetic model. 

A kinetic model which accounts for a multiplicity of active centres on supported catalysts has recently been developed. Computer simulations have been used to mechanistically validate the model and examine the effects on Its parameters by varying the nature of the distrlbultons, the order of deactivation, and the number of site types. The model adequately represents both first and second order deactivating polymerizations. Simulation results have been used to assist the interpretation of experimental results for the MgCl /EB/TlCl /TEA catalyst suggesting that... 

An analogous situation occurs in the catalytic cracking of mixed feed gas oils, where certain components of the feed are more difficult to crack (less reactive or more refractory) than the others. The heterogeneity in reactivities (in the form of Equations 3 and 5) makes kinetic modelling difficult. However, Kemp and Wojclechowskl (11) describe a technique which lumps the rate constants and concentrations into overall quantities and then, because of the effects of heterogeneity, account for the changes of these quantities with time, or extent of reaction. First a fractional activity is defined as... 

Torkelson and coworkers [274,275] have developed kinetic models to describe the formation of gels in free-radical pol5nnerization. They have incorporated diffusion limitations into the kinetic coefficient for radical termination and have compared their simulations to experimental results on methyl methacrylate polymerization. A basic kinetic model with initiation, propagation, and termination steps, including the diffusion hmitations, was found to describe the gelation effect, or time for gel formation, of several samples sets of experimental data. 

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