(496e) A Model-Based Systems Approach for Innovation in Integrated Chemical Product-Process Design | AIChE

(496e) A Model-Based Systems Approach for Innovation in Integrated Chemical Product-Process Design


Soni, V. - Presenter, Denmark Technical University
Rodriguez, R. M. - Presenter, Denmark Technical University
Conte, E. - Presenter, Denmark Technical University (DTU)

To be able to obtain specifically architectured chemicals it is advantageous to design the process and product simultaneously. The term product is used here for the chemically structured substance that facilitates the desired operations of a process. For example, a polymer for a membrane based separation process, a permeable film that could be used as a microcapsule for controlled release of pesticides or a pharmaceutical product, a chemical agent for a reaction system or a solvent for various types of solvent based separations. The highlight of the talk would be to describe a systematic product-process design framework for their simultaneous design. The design problem deals with design of the process to match the desired performance criteria by designing the structure of the products that match these performance targets. To do this, a design algorithm is proposed that would design products and processes simultaneously. This algorithm is based on the reverse design methodology, which has two major advantages over the more conventional forward approach. It is not only computationally inexpensive but also gives the opportunity of combining models that are multidisciplinary and multiscaled.

The algorithm is based on the idea that all processes depend on some properties of the products. These are the key properties of the system which affects the performance of the process. For example, reaction rate constant or dissociation constant for reactive systems, driving force for distillation or liquid-liquid extraction etc., thermodynamic or kinetic properties for solution diffusion kind of separation or selectivity of solvents for solvent based separation. Based on these assumptions, the algorithm splits the solution of the whole model describing the separation process into two stages. In the first stage the targets for properties are set, and this is done by setting the performance criteria (which is known) of the process and solving the process model with property parameters as the unknown variables. In the second stage, any appropriate property model can be used to obtain a list of products (in terms of their microscopic structural parameters) that matches the target properties (calculated in stage I). In this way, the hierarchal approach converges from the inlet and outlet specifications of a process to the product and process properties which ultimately leads to the microscopic structural design of products thus incorporating both macroscopic and microscopic aspects of the whole process in one framework. It is possible to have the products tailormade to suit the process demands by solution of integrated product and process models. It is important to highlight the introduction of multiscale concept when macroscopic and microscopic aspects are mentioned; because for some products the microscopic properties define the structure of the feasible chemical while the macroscopic properties are the end-use properties needed for process design.

The multiscale concept and integrated product process design will be highlighted through a case study of controlled release of active ingredients (AIs) from a polymeric microcapsule. A mathematical model describing the physical phenomena of the process integrated with predictive property models will be shown. The mathematical model of the microcapsule module is derived by dividing the whole module in three parts, namely, donor, membrane and receiver. The key properties that influence the process are solubility and diffusivity of pesticides through the microcapsule. In addition to these properties, the geometric parameters like area, thickness and volume of the microcapsule also influence the delivery rate. The design problem can conveniently be solved by reverse design algorithm by first calculating the key properties of the polymeric microcapsule given the amount of pesticide required to be released. In the second step different alternatives of polymers will be presented that possess these properties.