A field-based computer vision and corrosion sensor approach to study electrolyte dynamics in atmospheric corrosion

Abstract Transient electrolyte films govern atmospheric corrosion but remain difficult to monitor outdoors. Here, a novel field approach integrates imaging, environmental logging, AI and real-time corrosion sensing to capture data on surface wetting, weather and electrochemical response. Across multiple wetting events, incorporating image-derived electrolyte coverage improved prediction performance over a weather-only model. The approach enables linking electrolyte geometry with corrosion sensor signals, validating mechanistic models and comparing laboratory and field wetting.