Crystallization of Bis(2-hydroxyethylene) Terephthalate as a Part of a Bottle-to-Bottle Recycling Concept for Poly(ethylene terephthalate).

The chemical recycling of poly(ethylene terephthalate) (PET) is very attractive as PET bottle waste provides an abundant clean material with low levels of additives. One of the most promising processes is glycolysis, which depolymerizes PET in the presence of ethylene glycol. For this process, it is necessary to think through the whole concept, from the waste material to the newly polymerized virgin polymer. Most research ends with determining the yield of bis(2-hydroxyethyl)terephthalate (BHET) after glycolysis. Some research includes antisolvent crystallization with water to separate BHET from ethylene glycol. However, the subsequent separation of water and ethylene glycol is an energy-intensive process. Therefore, this work aims to directly crystallize BHET from ethylene glycol. For this reason, the crystallization of BHET was investigated experimentally. Crystallization was simulated using gPROMS Formulated Products with the aim of estimating kinetic parameters and using these to optimize an industrial process. Kinetic parameters were determined by model validation, including primary and secondary nucleation and crystal growth. The best-fitting set of kinetic parameters was used to optimize BHET crystallization in batch and continuous modes by minimizing equipment costs. Impeller parameters were found to have a great influence on crystallization performance. Ultimately, the continuous and batch processes gave comparable results in terms of equipment cost, with the batch process giving larger crystals and higher yields but the continuous process requiring a smaller crystallizer.

Integrated Filtration and Washing Modeling: Optimization of Impurity Rejection for Filtration and Washing of Active Pharmaceutical Ingredients.

A digital design tool that can transfer material property information between unit operations to predict the product attributes in integrated purification processes has been developed to facilitate end-to-end integrated pharmaceutical manufacturing. This work aims to combine filtration and washing operations frequently using active pharmaceutical ingredient (API) isolation. This is achieved by coupling predicted and experimental data produced during the upstream crystallization process. To reduce impurities in the isolated cake, a mechanistic model-based workflow was used to optimize an integrated filtration and washing process model. The Carman-Kozeny filtration model has been combined with a custom washing model that incorporates diffusion and axial dispersion mechanisms. The developed model and approach were applied to two systems, namely, mefenamic acid and paracetamol, which are representative compounds, and various crystallization and wash solvents and related impurities were used. The custom washing model provides a detailed evolution of species concentration during washing, simulating the washing curve with the three stages of the wash curve: constant rate, intermediate stage, and diffusion stage. A model validation approach was used to estimate cake properties (e.g., specific cake resistance, cake volume, cake composition after washing, and washing curve). A global systems analysis was conducted by using the calibrated model to explore the design space and aid in the setup of the optimization decision variables. Qualitative optimization was performed in order to reduce the concentration of impurities in the final cake after washing. The findings of this work were translated into a final model to simulate the optimal isolation conditions.

Digital Design of Filtration and Washing of Active Pharmaceutical Ingredients via Mechanistic Modeling.

To facilitate integrated end-to-end pharmaceutical manufacturing using digital design, a model capable of transferring material property information between operations to predict product attributes in integrated purification processes has been developed. The focus of the work reported here combines filtration and washing operations used in active pharmaceutical ingredient (API) purification and isolation to predict isolation performance without the need of extensive experimental work. A fixed Carman-Kozeny filtration model is integrated with several washing mechanisms (displacement, dilution, and axial dispersion). Two limiting cases are considered: case 1 where there is no change in the solid phase during isolation (no particle dissolution and/or growth), and case 2 where the liquid and solid phases are equilibrated over the course of isolation. In reality, all actual manufacturing conditions would be bracketed by these two limiting cases, so consideration of these two scenarios provides rigorous theoretical bounds for assessing isolation performance. This modeling approach aims to facilitate the selection of most appropriate models suitable for different isolation scenarios, without the requirement to use overly complex models for straightforward isolation processes. Mefenamic acid and paracetamol were selected as representative model compounds to assess a range of isolation scenarios. In each case, the objective of the models was to identify the purity of the product reached with a fixed wash ratio and minimize the changes to the crystalline particle attributes that occur during the isolation process. This was undertaken with the aim of identifying suitable criteria for the selection of appropriate filtration and washing models corresponding to relevant processing conditions, and ultimately developing guidelines for the digital design of filtration and washing processes.