Abstract
Acrylic resins are widely used as binder in coatings. A key sustainability goal for the production of this important class of polymer resins is to shift from non-renewable fossil-based to renewable (e.g. biobased) resources. To achieve this goal, two major challenges need to be addressed. First of all, new efficient production routes for acrylic resins containing a mix of different biobased functional units need to be developed. Secondly, a detailed understanding of the relationship between (i) the process conditions applied during production of the resin (and curing of the coating), (ii) the macromolecular structure (before and after curing) and (iii) the (cured) coating properties, needs to be obtained.
Focusing on solvent-borne coatings, solutions for these two challenges are provided in this project by (i) introducing new functionalization strategies for biobased acrylic platform monomers and (ii) systematically unravelling process-structure-property relationships via a newly developed multiscale machine learning supported workflow.
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