A Review on Advanced AFM and SKPFM Data Analytics for Quantitative Nanoscale Corrosion Characterization

Corrosion is a complex, surface-initiated process that demands nanoscale, real-time characterization to understand its initiation and propagation. Atomic Force Microscopy (AFM) and Scanning Kelvin Probe Force Microscopy (SKPFM) have emerged as powerful tools in corrosion science, enabling high-resolution imaging and electrochemical mapping under realistic conditions. This review, inspired by pioneering work at KTH by Professors Christofer Leygraf and Jinshan Pan, highlights advanced analytical strategies that extend the capabilities of AFM and SKPFM beyond traditional line-profile analysis. Techniques such as power spectral density (PSD) analysis, multimodal Gaussian histogram fitting, statistical roughness quantification, and deconvolution methods are discussed in the context of case studies on aluminum alloys, stainless steels, magnesium alloys, biomedical implants, and protective coatings. By integrating in-situ imaging, electrochemical mapping, and statistical data processing, these approaches provide deeper insights into localized corrosion, micro-galvanic coupling, and surface reactivity. Future directions include coupling AFM-based methods with high-speed imaging, machine learning, and spectro-electrochemical techniques to accelerate the development of corrosion-resistant materials and predictive diagnostics.