A Multi-Analytical Approach to the Study of Structure-Property Relationships in Epoxy-Amine Thermosetting Coatings.

Anti-corrosion primers required for all steel surfaces are most commonly epoxy-amine based due to their exceptional durability, adhesion, and resistance to moisture and chemicals. The types of epoxies and amines are tailored to meet specific performance requirements, with the catalyst DMP-30 often added for its superior drying acceleration. Many improvements in formulation science traditionally stem from empirical experimentation whereby additives such as DMP-30 enhance performance (drying or mechanical properties) without a complete understanding of the underlying mechanisms. This thesis aimed to elucidate the effects of catalysts and relative stoichiometries of amine to epoxy on network formation and material properties. The properties of various epoxy-amine thermosetting systems are analysed using three key techniques: near infrared (NIR) spectroscopy, drying time analysis and differential scanning calorimetry (DSC). This multi-analytical approach allows insight into the intricate relationships between network structure and the resulting material properties, including extent and rate of conversion of reactive groups, drying performance and glass transition temperature (Tg). This research demonstrates that fast reaction kinetics cannot be presumed to correlate with fast drying, suggesting that network architecture formed under specific conditions has a greater impact on gelation and drying events than reaction rate alone. This work establishes a methodology for real-time analysis of both network forming and non-network forming epoxy-amine systems, enabling calculation of initial rates and overall conversion of epoxide as a function of time or temperature, while correlating drying events to extent of conversion. Additionally, this thesis demonstrated the significance of the Tg-conversion relationship in thermosetting epoxy-amine materials for predicting material property evolution. The Gillham-Venditti (GV) model was adapted and applied to experimentally measured Tg and conversion data validating its applicability to amine deficient and catalysed formulations. The GV method requires only two Tg values - Tg (0) and Tg (∞) – along with the change in heat capacity (ΔCp) at each point to accurately predict the complete Tg-conversion relationship. This method proved suitable for most of the twelve formulations studied, offering significant implications for screening industrially relevant formulations and gathering comprehensive information on Tg development with conversion, including temperature implications for Tg, vitrification temperature, and curing temperature (Tcure), from approximately 50 minutes of analysis time.