(241c) Managing the Complexity in Liquid Formulation Design | AIChE

(241c) Managing the Complexity in Liquid Formulation Design


Conte, E. - Presenter, Denmark Technical University (DTU)
Gani, R. - Presenter, Department of Chemical and Biochemical Engineering, Technical University of Denmark (DTU)

The present day chemical industry is evolving beyond commodities towards specialty chemicals and consumer oriented chemical based products. Formulated products such as shampoos, paints, sunscreens, hair sprays enter in this last category of consumer oriented products. They are constituted by Active Ingredients (AIs), solvents and additives and in order to be commercially successful they need to meet many and often conflicting requirements of the market. This shift in the chemical industry is not simply a change from commodities to specialties [1], but a substantial innovation from material valued for their purity, to materials sold for their performance behaviour [2]. This evolution in the market has to be followed by an evolution in the product design discipline. Involving very different chemicals, formulations are complex products which make the modelling effort challenging. The ?scientific part' of chemical engineering consists of breaking down such complex systems into subsystems and to understanding the fundamental concepts associated to the behaviour of chemicals in solution. The ?engineering part' of chemical engineering consists in applying the gained knowledge in the design of a formulated product which matches the desired characteristics, and a process which is capable of producing it [3], although in liquid formulations, the processing part may not be as demanding as the structured chemical products. The development of systematic methodologies, tools and strategies is crucial in order to organize, systematize and improve the design and evaluation of complex systems for the production of chemical products [3]. A common practice is still the experiment-based trial-and-error approach. Model-based computer-aided tools which perform a fast screening of numerous candidates and alternatives could drastically reduce time and resources by providing ?virtual and focused? experimentation possibilities. The virtual Product and Process Design laboratory (virtual PPD-lab) [4-5] provides a hybrid approach to product and process design, where focused virtual experimentations coupled with systematic generation and screening of chemical product alternatives can be performed. Through the virtual PPD-lab the product (formulation) developer can ask for the generation of a short list of the most promising feasible candidates (generation of alternatives) and also test some of his/her ideas (candidate formulations) through validated model-based computer-aided tools. The experimental resources, in this way, are reserved for the final selection and verification step, after a set of promising candidates have been identified, thereby achieving faster to market at reduced cost for any potential chemicals based product (formulation). Tailor made work-flows for design of specific products have already been developed and incorporated in the virtual PPD-lab software. A work-flow for the design of liquid formulated products has been developed and tested for the systematic generation and screening of alternatives in the design of paints [4], insect repellents and sunscreens [5]. The aim of this paper is to illustrate the power of the virtual PPD-lab in performing virtual experiments in relation to an industrial case study on hair spray. Given the AIs, a list of feasible solvents and the additives, a suitable solvent mixture matching the a priori defined targets needs to be identified. However, before the design problem can be solved appropriate property-mixing models need to be generated. This is because the AIs involved are polymers and appropriate property models helping to understand their phase behavior with solvents first needs to be developed and implemented into the virtual PPD-lab software. Once the models have been added to the model library of the virtual PPD-lab, the established work-flow (algorithm) for liquid formulation design is applied to determine the optimal product. The case study is an excellent example to illustrate how the virtual PPD-lab can help to manage the complexities associated with the design of industrial products as well as to reducing the experimental costs. The complexities involved consist of molecular design (candidates for solvents and additives), mixture design (liquid formulations) and testing of complex multicomponent phase behavior.

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