The polymer reaction engineering research is closely related to the polymer industry. Our goal is to contribute to the progress of industrial polymerization process technology through fundamental research in polymerization kinetics, reactor design and analysis, process optimization and control. In fact, many of our research ideas come from our interaction with polymer industries. Instead of trying to develop commercial polymerization process technology, we aim at developing a fundamental understanding of underlying chemical and physical phenomena and also generating new scientific knowledge and data.
In the past years, we have collaborated with many chemical companies in various research areas. The following is a list of major chemical companies who supported our research directly and indirectly through Chemical Process Systems Research Laboratory (A consortium of chemical companies operated jointly by Profs. T.J. McAvoy and E. Zafiriou)
ˇ Exxon Chemical Company
ˇ Dow Chemical Company
ˇ Eastman Chemical Company
ˇ Rhone-Poulenc (France)
ˇ Solvay (Belgium)
ˇ LG Chemical Company (Korea)
ˇ Rhodia-ster (Brazil)
ˇ Shell Chemical Company
The examples of research projects with these companies include:
ˇ Modeling of metallocene catalyzed homogeneous polymerization reactors
ˇ Modeling of gas phase fluidized bed olefin polymerization reactors
ˇ Modeling of chromium oxide catalyzed olefin polymerization kinetics and
ˇ Modeling of slurry phase high density ethylene polymerization reactors
ˇ Modeling of high pressure LDPE polymerization reactors
ˇ Modeling of poly(vinyl chloride) reactors
ˇ Modeling of melt polycondensation reactors for polyesters and polycarbonates
ˇ Metallocene catalyzed polymerization kinetics and process design
ˇ Photodegradable polyethylene
ˇ On-line estimation and control of polymerization reactors
Why modeling in many industrial projects?
Mathematical models are very important tools in the polymer industry not only for the design of new polymerization processes but also for the advancement of reactor controls. The mathematical model of a process helps engineers better understand how the plant or process will behave when certain process parameters are changed or when process disturbances are introduced. Although there are some commercially available process simulation packages, some companies prefer customized process models to the general models available in such commercial packages. A detailed process model can be used to evaluate process control options or to design optimal process control systems even before a plant is built. The process models give deep physical insights into the process characteristics, which will allow the engineers to develop improved or new process technology.