Polymerization processes, optimization

A comprehensive review of the broad aspects of polymerization process modeling and its applications is not the objective here. In this entry, some critical issues related to the modeling, design, and control of polymerization reactors are discussed with some examples to illustrate modeling techniques and their applications to polymerization process optimization and control. 

The chemical modification of polymers is a post polymerization process which is used in certain situations i) to improve and optimize the chemical and mechanical properties of existing polymers or ii) to introduce desirable functional groups in a polymer. 

In solution polymerization, monomers mix and react while dissolved in a suitable solvent or a liquid monomer under high pressure (as in the case of the manufacture of polypropylene). The solvent dilutes the monomers which helps control the polymerization rate through concentration effects. The solvent also acts as a heat sink and heat transfer agent which helps cool the locale in which polymerization occurs. A drawback to solution processes is that the solvent can sometimes be incorporated into the growing chain if it participates in a chain transfer reaction. Polymer engineers optimize the solvent to avoid this effect. An example of a polymer made via solution polymerization is poly(tetrafluoroethylene), which is better knoivn by its trade name Teflon . This commonly used commercial polymer utilizes water as the solvent during the polymerization process,... 

A continuous bulk polymerization process with three reaction zones in series has been developed. The degree of polymerization increases from the first reactor to the third reactor. Examples of suitable reactors include continuous stirred tank reactors, stirred tower reactors, axially segregated horizontal reactors, and pipe reactors with static mixers. The continuous stirred tank reactor type is advantageous, because it allows for precise independent control of the residence time in a given reactor by adjusting the level in a given reactor. Thus, the residence time of the polymer mixtures can be independently adjusted and optimized in each of the reactors in series (8). 

Researchers at Bayer AG addressed these critical issues and developed successful solutions enabling commercial application of Julia-Colonna-type epoxidation [35-40]. Starting with optimization of catalyst preparation, a straightforward synthesis based on inexpensive reagents and requiring a shorter reaction time was developed for the poly-Leu-catalyst [35], In particular, the reaction time for the new polymerization process was only 3 h when the process was conducted at 80 °C in toluene, compared with 5 days under classic reaction conditions (THF, room temperature). Furthermore, the catalyst prepared by the Bayer route is much more active and does not require preactivation [35-40],... 

Continuous emulsion polymerization processes are presently employed for large scale production of synthetic rubber latexes. Owing to the recent growth of the market for polymers in latex form, this process is becoming more and more important also in the production of a number of other synthetic latexes, and hence, the necessity of the knowledge of continuous emulsion polymerization kinetics has recently increased. Nevertheless/ the study of continuous emulsion polymerization kinetics hasf to datef received comparatively scant attention in contrast to batch kinetics/ and very little published work is available at present/ especially as to the reactor optimization of continuous emulsion polymerization processes. For the theoretical optimization of continuous emulsion polymerization reactors/ it is desirable to understand the kinetics of emulsion polymerization as deeply and quantitatively as possible. 

Polymer properties are very often dependent on the polymer preparation. So, a good monitoring of the polymerization process is the key step to obtaining good and reproducible materials. The extent of the polymerization can be controlled in different ways. IR is the most usual [27,30] but is not very accurate and requires the extraction of samples to analyze. Recently, an in situ monitoring of PMR-15 processing has been provided by means of frequency-dependent dielectric measurements [33,34]. This non-destructive technique allows the characterization of all the steps of the curing process and thus they can be optimized. 

When choosing the kinetic model of a particular polymerization process an engineer-researcher inevitably faces the necessity to proceed from two opposite considerations. On the one hand, he is interested in the maximal simplicity of this model bearing in mind the analysis of the results obtained on the basis of such a model and the subsequent solution of optimization problems. On the other hand, he is perfectly aware of the... 

The final aqueous detritylation is a complicated step that requires careful process optimization, such as control of pH, oligo and salt concentrations etc. 49 After detritylation, the oligonucleotide is precipitated quantitatively from the acidic DMT cation containing solution under optimized conditions. This step can be labor intensive at the large scale, and may be inconvenient for the high-throughput small-scale synthesis. One way to circumvent the problem is to use on column detritylation, where the RP and detritylation steps are combined in one chromatographic operation. Since the acid can leach the silica based columns, this is more useful on polymeric supports. 

The polymerization process can be carried out as a batch, semibatch, or continuous process. This offers the possibility to optimize reaction conditions and obtain microgels with desired properties. 

The main features of inverse microemulsion polymerization process have been reviewed with emphasis given to a search for an optimal formulation of the systems prior to polymerization. By using cohesive energy ratio and HLB concepts, simples rules of selection for a good chemical match between oils and surfactants have been established this allows one to predict the factors which control the stability of the resultant latices. The method leads to stable uniform inverse microlatices of water-soluble polymers with high molecular weights. These materials can be useful in many applications. 

MacGregor and Tidwell (1979) illustrate some of the steps involved in running plant experimentation, building these process and disturbance models, and implementing simple optimal controllers on some continuous condensation polymerization processes. A number of similar applications to continuous emulsion polymerization processes have also been made. 

One alternative to the direct online measurement of polymer properties is to use a process model in conjunction with optimal state estimation techniques to predict the polymer properties. Indeed, several online state estimation techniques such as Kalman filters, nonlinear extended Kalman filters (EKF), and observers have been developed and applied to polymerization process systems. ° In implementing the online state estimator, several issues arise. For example, the standard filtering algorithm needs to be modified to accommodate time-delayed offline measurements (e.g., MWD, composition, conversion). The estimation update frequency needs to be optimally selected to compensate for the model inaccuracy. Table 5 shows the extended Kalman filter algorithm with delayed offline measurements. Fig. 2 illustrates the use of online state estimator... 

Crowley, T.J. Choi, K.Y. Discrete optimal control of molecular weight distribution in a batch free radical polymerization process. Ind. Eng. Chem. Res. 1997, 36, 3676-3684. 

Butala, D.N. Liang, W.R. Choi, K.Y. Multiobjective dynamic optimization of batch free radical polymerization process by mixed initiator systems. J. Appl. Polym. Sci. 1992, 1759-1778. 

Curteanu, S., Leon, F., Galea, D. (2006). Alternatives for multi-objective optimization of a polymerization process, J. Appl. Polym. Sci., 100, pp. 3680-3695. 

Massebeuf, S., Fonteix, C., Hoppe, S. and Pla, F. (2003). Development of new concepts for the control of polymerization processes multiobjective optimization and decision engineering. I. Application to emulsion homopolymerization of styrene, J. Appl. Polym. Sci, 87, pp. 2383-2396. 

Mitra, K., Majumdar, S. and Raha, S. (2004a). Mnlti-objective d3mamic optimization of a semi-batch epoxy polymerization process, Comput. Chem. Eng., 28, pp. 2583-2594. 

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