Analysing the Coupled Effects of Compressive and Diffusion Induced Stresses on the Nucleation and Propagation of Circular Coating Blisters in the Presence of Micro-cracks.

Abstract

This paper presents the delamination of coating with micro-cracks under compressive residual stress coupled with diffusion induced stress. Micro-cracks in coating provide a passage for corrosive species towards the coating-substrate interface which in turn produces diffusion induced stress in the coating. Micro-cracks contract gradually with increasing compressive residual stress in coating due to thermal expansion mismatch which blocks the species diffusion towards the interface. This behaviour reduces the diffusion induced stress in the coating while the compressive residual stress increases. With further increase in compressive residual stress, micro-cracks reach to the point, where they cannot be constricted any further and a high compressive residual stress causes the coating to buckle away from the substrate resulting in delamination and therefore initiating blistering. Blistering causes the contracted micro-cracks to wide open again which increases diffusion induced stress along with high compressive residual stress. The high resultant stress in coating causes the blister to propagate in an axis-symmetric circular pattern. A two-part theoretical approach has been utilised coupling the thermodynamic concepts with the mechanics concepts. The thermodynamic concepts involve the corrosive species transportation through micro-cracks under increasing compression, eventually causing blistering, while the fracture mechanics concepts are used to treat the blister growth as circular defect propagation. The influences of moduli ratio, thickness ratio, thermal mismatch ratio, poisson’s ratio and interface roughness on blister growth are discussed. Experiment is reported for blistering to allow visualisation of interface and to permit coupled (diffusion and residual) stresses in the coating over a full range of interest. The predictions from model show excellent, quantitative agreement with the experimental results.