Computer-Aided Design of Paints and Coatings – A review and recent applications
Georgios M. Kontogeorgis*, Spardha Jhamb, Xiaodong Liang, Kim Dam-Johansen
CERE and CoaST, Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 229, Søltofts Plads 229, DK – 2800, Kgs. Lyngby, Denmark
*Corresponding author
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Computer-aided design (CAD) is still in an early stage in the paints and coatings industrial sector and its potential is yet to be utilised to the maximum. Nevertheless, Computer-aided tools offer many possibilities in the design of paints and coatings. Significant advances have been made, involving also the use of thermodynamic and other property models for the study and theoretical formulation of these products. Algorithms and tools based on such models enable the formulation chemist to speed up the design process, by allowing them to focus their experimental efforts on a selected number of reliable constituents for the coating formulation. The final validation should still be done using experiments.
In this presentation, we first briefly present some literature studies in the field of CAD for paints and coatings, which are based on physicochemical property models or on machine learning algorithms and high-throughput experimentation.
Next, we turn our focus on the selection of solvents and calculation of their composition in the final product, which is a critical step in coating formulation design. This task can be greatly facilitated by computer-aided methods if the necessary thermodynamic and group contribution property models along with chemical property data are available for the ingredients under consideration. We will show that the computer-aided stage can be used to speed-up the solvent selection and design process, efficiently utilize experimental resources and serve as a guide for the formulation chemist.
We will particularly illustrate in this work an adaption of the generic Computer-Aided Product Design (CAPD) methodology for organic coating formulations with focus on the design of solvents for coatings. The applicability of this framework will be tested via case studies with industrial interest which involve a variety of pigments, solvents and polymers.
The scope of using the computer-aided design algorithms is limited by the availability, reliability and accuracy of the models employed to predict the target properties. Limitations of the current framework and future directions will also be outlined.