Reactor monomer conversion

Continuous stirred tank reactors are used commercially for solution, bulk (mass), and emulsion polymerization of vinyl monomers. In bulk homogeneous polymerization processes (e.g., polystyrene), the reactor system usually consists of a single CSTR or multiple CSTRs and an extruder-type devolatilizer to remove unreacted monomer, which is then recycled to the reactor. As monomer conversion increases, the viscosity of the polymerizing fluid increases and the overall heat removal efficiency decreases. When styrene is polymerized in bulk in a stirred tank reactor, monomer conversion is limited to about 30-40% due to an increasing viscosity of the polymerizing fluid above this conversion level. However, the overall monomer conversion can be very high because unreacted monomer is constantly recycled to the reactor. 

The production rate is 2—4 t/h, depending on the feed rate, monomer concentration in the feed, and conversion. The conversion of isobutylene and isoprene typically ranges from 75—95% and 45—85%, respectively, depending on the grade of butyl mbber being produced. The composition and mol wt of the polymer formed depend on the concentration of the monomers in the reactor Hquid phase and the amount of chain transfer and terminating species present. The Hquid-phase composition is a function of the feed composition and the extent of monomer conversion. In practice, the principal operating variable is the flow rate of the initiator/coinitiator solution to the reactor residence time is normally 30—60 minutes. 

The reaction rate in a continuous reactor is dependent on monomer conversion but it does not vary with time once steady-state... 

Figure 4. Monomer conversion vs. time of polymerization of styrene in a hatch reactor agitation speed as parameter...

Figure 7. Monomer conversion vs, polymerization time in the helical tubular reactor laminar flow regime...

Figure 10. Monomer conversion rates as a function of emulsion Reynolds number for straight and helical tubular reactors...

Reactor Conditions for Experimental Runs. Operating conditions for the continuous, stirred tank reactor runs were chosen to study the effects of mixing speed on the monomer conversion and molecular weight distribution at different values for the number average degree of polymerization of the product polymer. 

The experimental monomer conversion and degrees of polymerization for the continuous reactor runs are given in Table IV. 

Initial comparison of CFSTR runs with similar feed conditions indicates conditions for which the monomer conversion may be dependent on mixing speed. However, when the effects of experimental error in monomer conversion and differences in reaction temperature are considered, the monomer conversion is seen to be relatively independent of mixing speed for rpm equal to or greater than 500. Comparing Run 14 with Run 12 reveals a small decrease in monomer conversion in spite of a rise in reactor temperature of 2°C. This indicated the presence of a small amount of bypassing or dead volume at the lower mixing speed. This imperfect mixing pattern would also be present in Run 15. 

The micro-mixed reactor with dead-polymer model was developed to account for the large values of the polydispersity index observed experimentally. The effect of increasing the fraction of dead-polymer in the reactor feed while maintaining the same monomer conversion is to broaden the product polymer distribution and therefore to increase the polydispersity index. As illustrated in Table V, this model, with its adjustable parameter, can exactly match experiment average molecular weights and easily account for values of the polydispersity index significantly greater than 2. 

The effect of dead-polymer and by-passing on the micro-mixed reactor for the same degree of monomer conversion is to broaden the product polymer distribution and thus allow values of the polydispersity index much larger than 2. 

FIGURE 13.7 Performance of a laminar flow, tubular reactor for the bulk polymerization of styrene Tin = 35°C and F = 1 h. (a) Stability regions, (b) Monomer-conversion within the stable region. 

This paper presents the physical mechanism and the structure of a comprehensive dynamic Emulsion Polymerization Model (EPM). EPM combines the theory of coagulative nucleation of homogeneously nucleated precursors with detailed species material and energy balances to calculate the time evolution of the concentration, size, and colloidal characteristics of latex particles, the monomer conversions, the copolymer composition, and molecular weight in an emulsion system. The capabilities of EPM are demonstrated by comparisons of its predictions with experimental data from the literature covering styrene and styrene/methyl methacrylate polymerizations. EPM can successfully simulate continuous and batch reactors over a wide range of initiator and added surfactant concentrations. 

Data of Nomura and Funita (12). The predictive capabilities of EPM for copolymerizations are shown in Figures 8-9. Nomura has published a very extensive set of seeded experimental data for the system styrene-MMA. Figures 8 and 9 summarize the EPM calculations for two of these runs which were carried out in a batch reactor at 50 °C at an initiator concentration of 1.25 g dm 3 water. The concentration of the seeded particles was 6x10 dm 3 and the total mass of monomer was 200 g dm 3. The ratio of the mass of MMA to the total monomer was 0.5 and 0.1 in Figures 8 and 9 respectively. The agreement between the measured and predicted values of the total monomer conversion, the copolymer composition, and the concentration of the two monomers in the latex particles is excellent. The transition from Interval II to Interval III is predicted satisfactorily. In accordance with the experimental observations, EPM predicted no new particle formation under the conditions of this run. 

In this work, a comprehensive kinetic model, suitable for simulation of inilticomponent aiulsion polymerization reactors, is presented A well-mixed, isothermal, batch reactor is considered with illustrative purposes. Typical model outputs are PSD, monomer conversion, multivariate distritution of the i lymer particles in terms of numtoer and type of contained active Chains, and pwlymer ccmposition. Model predictions are compared with experimental data for the ternary system acrylonitrile-styrene-methyl methacrylate. 

Afterwards, the PP powder is fluidized by a mixture of ethylene, propylene and inert gas (propane) in the fluid bed reactor, FBR, which is cooled by convective gas flow. The monomer conversion per gas circulation is limited to a few percent, because of the adiabatic temperature rise of more than 10 K per % conversion. Neglecting the heat loss through the reactor wall and through the product withdrawal, and assuming a well mixed reactor, the heat removal capacity of a steady-state FBR limits the productivity and can be expressed by... 

Figure 4.26. Profiles of monomer conversion along a reactor.

Comparison between Experimental Results and Model Predictions. As will be shown later, the important parameter e which represents the mechanism of radical entry into the micelles and particles in the water phase does not affect the steady-state values of monomer conversion and the number of polymer particles when the first reactor is operated at comparatively shorter or longer mean residence times, while the transient kinetic behavior at the start of polymerization or the steady-state values of monomer conversion and particle number at intermediate value of mean residence time depend on the form of e. However, the form of e influences significantly the polydispersity index M /M of the polymers produced at steady state. It is, therefore, preferable to determine the form of e from the examination of the experimental values of Mw/Mn The effect of radical capture mechanism on the value of M /M can be predicted theoretically as shown in Table II, provided that the polymers produced by chain transfer reaction to monomer molecules can be neglected compared to those formed by mutual termination. Degraff and Poehlein(2) reported that experimental values of M /M were between 2 and 3, rather close to 2, as shown in Figure 2. Comparing their experimental values with the theoretical values in Table II, it seems that the radicals in the water phase are not captured in proportion to the surface area of a micelle and a particle but are captured rather in proportion to the first power of the diameters of a micelle and a particle or less than the first power. This indicates that the form of e would be Case A or Case B. In this discussion, therefore, Case A will be used as the form of e for simplicity. 

The available data from emulsion polymerization systems have been obtained almost exclusively through manual, off-line analysis of monomer conversion, emulsifier concentration, particle size, molecular weight, etc. For batch systems this results in a large expenditure of time in order to sample with sufficient frequency to accurately observe the system kinetics. In continuous systems a large number of samples are required to observe interesting system dynamics such as multiple steady states or limit cycles. In addition, feedback control of any process variable other than temperature or pressure is impossible without specialized on-line sensors. This note describes the initial stages of development of two such sensors, (one for the monitoring of reactor conversion and the other for the continuous measurement of surface tension), and their implementation as part of a computer data acquisition system for the emulsion polymerization of methyl methacrylate. 

Several control techniques have been developed to compensate for large dead-times in processes and have recently been reviewed by Gopalratnam, et al. (4). Among the most effective of these techniques and the one which appears to be most readily applicable to continuous emulsion polymerization is the analytical predictor method of dead-time compensation (DTC) originally proposed by Moore ( 5). The analytical predictor has been demonstrated by Doss and Moore (6) for a stirred tank heating system and by Meyer, et al. (7) for distillation column control in the only experimental applications presently in the literature. Implementation of the analytical predictor method to monomer conversion control in a train of continuous emulsion polymerization reactors is the subject of this paper. 

The analytical predictor, as well as the other dead-time compensation techniques, requires a mathematical model of the process for implementation. The block diagram of the analytical predictor control strategy, applied to the problem of conversion control in an emulsion polymerization, is illustrated in Figure 2(a). In this application, the current measured values of monomer conversion and initiator feed rate are input into the mathematical model which then calculates the value of conversion T units of time in the future assuming no changes in initiator flow or reactor conditions occur during this time. 

X3 = monomer conversion from third reactor in series Subscripts... 

---