Modeling and Optimization of Distillation Column for Separation of 18O Isotope with Mathematical Model

Positron emission tomography (PET) is an advanced imaging tool for the diagnosis and staging of cancer tumors. This method is based on the detection of increased glycolytic activity in malignant cells, in which cell glucose is concentrated because of an increase in membrane glucose transporters, as well as an increase in some key enzymes, such as hexokinase, which are responsible for glucose phosphorylation. Therefore, for this type of imaging, drugs containing glucose are needed. On the other hand, with the expansion of the use of PET imaging devices, the need for drugs for this type of imaging method [fluorodeoxyglucose drug (FDG)] has also increased significantly. FDG is a drug tracer used in the medical imaging technique of PET. The production of FDG requires the production of F-18 and, as a result, reaching O-18 with a richness of more than 95%. There are various methods to produce oxygen with high richness. Among these methods, using a distillation column is a suitable method to produce oxygen, which has low efficiency and high production cost. Optimization of the distillation column can reduce the cost of producing high-rich oxygen. Numerical methods are one of the useful techniques for optimization. In this study, the distillation column has been computerized using mathematical models, and then by changing the number of inputs, including the height of the pipes, the temperature of the input of the distillation column has been optimized. Results show that the maximum separation of the desired isotope concentration in the distillation tower depends on the type of isotope desired and the condition of the device and is independent of the type of feed. Also, the input feed has no effect on the concentration distribution.