The project is coordinated by Dr David Dubbeldam, an associate professor and Vidi laureate at the Computational Chemistry group of the UvA’s Van ‘t Hoff Institute for Molecular Sciences. It builds on earlier research of Prof. Piet Iedema, now professor emeritus, in the field of Computational Polymer Chemistry. It also entails cooperation with Vidi laureate Dr Ivan Kryven, who worked at the Iedema group and now is an assistant professor at the Mathematical Institute of Utrecht University, focusing on mathematical modelling, complex networks and mathematical chemistry. Industrial partners are Canon Production Printing (Venlo), AkzoNobel Performance Coatings (Sassenheim), Reden (Engineering and simulation, Hengelo OV) and the Rijksmuseum. Including the contribution from industry, the total project budget is just over a million euros.
The project acronym derives from PROperty prediction by Network TOpology modelling of polymer films. The formation of such films is an intriguing and complex process. They result from the ‘drying’ of paints or coating solutions which is in fact a solidification process where multifunctional monomers in the liquid polymerize into a polymer network that can be viewed as a single large molecule spanning the entire volume. Although qualitatively well-understood, accurate quantitative prediction of this process is a major modelling challenge. In particular, it has to take into account the rates of reactions and diffusion that define the network formation, while these rates are dramatically influenced by the density of the growing network. To address this complexity, the PRONTO researchers will develop multiscale computational models connecting atomic-level molecular simulations, mesoscopic reaction kinetics and network modelling, and macroscopic continuum modelling. The combined efforts of three PhD candidates will lead to a more fundamental and detailed understanding of polymer network formation and provide means for quantitative prediction.
An important goal of PRONTO is to develop a practical aid for predicting, controlling, and preserving visual appearance and mechanical properties of thin films (10-300 μm) in several areas of application. For instance, in fast and continuous industrial printing, the quality of a print is affected by various conditions, where drying/solidifying ink with UV light is a major issue. Models that quantitively describe the printing process can provide the key to improve printer performance with respect to print quality (e.g. colour and gloss) and mechanical aspects (e.g. robustness and flexibility). In the development of paint resins, PRONTO will contribute to the development of models that are available to predict morphology and thermo-mechanical properties of final paint layers, based on atomistic structure morphology and its dynamics on a microscopic level. Finally, in the field of art restoration and conservation the developed models can help understand and control the chemical complexity of aging oil paintings so that their original brilliant appearance can be preserved or restored.