Development of a new paint starts with a problem statement. A sample is then created for testing, and the formulation is revised according to the results.
This resource intensive cycle continues with increasingly small optimization steps as the difference between the paint properties and targeted specifications decrease. Computer-aided product design (CAPD) of coatings can find suitable formulations by matching the targeted specifications, and choosing or designing matching components such as pigments, polymers and solvents.
The aim for this project is to use CAPD - a combination of computational tools, algorithms, databases, and predictive methods – to solve a wide range of design problems for paints and coatings. This project will initially develop property estimation methods and databases for pigments and polymers, in cooperation with a PhD project by Spardha Jhamb who focuses on solvents. The final stages depend on the outcome of current research.
The full scope of product design includes experimental planning and verification, but the focus of this project is problem specification and design through modelling and tools. To test the viability of the design, verification of the computational framework’s ability of solving a large range of design problems will be studied through case studies with various needs and specifications.
Related Phd projects: A Systematic Methodology for Property Model-Based Chemical Substitution and Chemical Formulation Design