A modelling approach to study the microstructure and leaching behaviour of active protective coatings

Abstract

Organic coatings protect metals from corrosion by acting as a barrier between the substrate and the environment. In addition to this passive mechanism, primer coatings also contain active corrosion inhibitors that leach out of the paint upon exposure to moisture and interfere with the corrosion reactions. Chromate-based inhibitors have been employed for decades due to their excellent corrosion protection properties, but are toxic and need to be replaced, although few alternatives show promising properties. However, the research has highlighted that the protection performance of a primer does not depend only on the effectiveness of the corrosion inhibitor, but also on the leaching kinetics. In addition, the process of inhibitor leaching is affected by the coating microstructure, which, in turn, is influenced by the coating formulation. This suggests the possibility to design optimised, chromate-free coatings by tuning their composition and microstructure in order to control the leaching of inhibitors and the protection performance during the service life. However, the relationship between formulation, microstructure and leaching kinetics is complex and still the object of research. The aim of this thesis is the development of a modelling approach to investigate the microstructure and leaching behaviour of primers, as a function of the coating formulation. The research methodology is based on the generation of virtual representations of coatings with given formulation parameters and on the subsequent simulation of the leaching process using the Cellular Automata method. The virtual coatings were characterised with suitably defined descriptors to investigate the effect of the formulation on the features of the pigment clusters, which are fundamental to the leaching mechanism. The analysis demonstrated the percolating nature of the clusters and suggested the importance of the percolation threshold as a critical factor in the design of a coating. The results of the microstructure characterisation and leaching simulation suggested that intervening on the pigment volume concentration and on the particles attributes (such as size distribution and shape) can be an effective way to control the properties and improve the performance of a primer. Furthermore, this work demonstrated the feasibility of a modelling approach in studying active protective coatings and suggested its potential applicability as a tool in the development of new formulations.

Date of Award	1 Aug 2021
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Xiaorong Zhou (Supervisor) & Flor Siperstein (Supervisor)