Electrochemical behaviour of organic coating defects.

Abstract

The electrochemistry of artificial defects with a range of diameters between 100 and 2000 microns created user a laser etching technique on a model clearcoat epoxy system with a thickness of 30 microns has been studied using various methods with a focus on impedance methods such as EIS and local EIS in pursuit of creating a predictive Finite Element model for a defective coating. The exposed surface area was characterised using laser confocal microscopy allowing for a quantitative analysis of the artificial defects and the accounting for of any imperfections such as residual coating through area exclusions in the surface area calculations. Various methods were trialled such as mechanical deformations with the final chosen method being laser ablation due to its effective and accurate formation of artificial defects with minimal damage to the mild steel substrate, albeit with thermal degradation to the nearby coating. Through experimental characterisation of the two extreme conditions, being bare substrate and a completely intact coating, the intention was to predict the electrochemical character of the continuum between these situations. The bare substrate was characterised using EIS to extract double-layer capacitance and charge-transfer resistance with PDP measurements to characterise the redox processes outside of the pseudo-linear region probed by EIS. The intact coating was measured via EIS to estimate the capacitance of the organic coating and in turn, the relative permittivity of the coating upon saturation with electrolyte and stabilisation of the dielectric behaviour. These parameters could then be used to develop the Finite Element model, which would then be used to predict the electrochemical behaviour of defined artificial defects in pursuit of validating the model. Local EIS was intended to allow the impedance of specific regions of an artificially defective coating system to be measured, allowing for discrepancies in model predictions to be identified and then localised to specific regions, allowing for much more effective troubleshooting. This was ultimately not possible due to the use of a remote reference electrode and the necessity for a low conductivity solution resulting in unreliable measurement of the pseudo-linear region around the open-circuit potential. These results were then repurposed along with a corresponding model developed to explore the fundamentals of the method in pursuit of supporting future work using local EIS. The global EIS model has provided insights into the functioning of coating defects such as a reduced relative charge-transfer resistance at reduced sizes, believed to be as a result of increased radial diffusion of oxygen. The validation of the model for all defect sizes was complex due to the presence of competitive electrochemically active sites throughout the coating which often offered a lower impedance pathway to the artificial defects created and replicated in the model. These sites are often characterised by a Randles-circuit style behaviour with a high pore resistance and charge-transfer resistance due to their expected tortuosity. This results in the artificial defect often being measurable at higher frequencies where it offers a lower impedance pathway relative to the pore resistance of these other sites. These sites have been termed Active Coating Regions and have been investigated by EIS and have been found to be a random population throughout the coating with a total number of sites which increases with the surface area of the coating. While these sites often exhibit Randles-circuit style behaviour, which would be expected of holes or simply exposed substrate in general, these are believed to cover a wider range of non-ideal regions. Examples include ACR which exhibit serial RC behaviour due to potential charge-transfer resistance being too high to be a preferable pathway. These sites are often accompanied by a measurable open-circuit potential, suggesting that an electr

Date of Award	1 Aug 2025
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Stuart Lyon (Supervisor) & Nicholas Stevens (Supervisor)