Understanding localized corrosion under atmospheric droplets is critical, yet previous studies have mostly focused on single-droplet systems or general trends, leaving the role of individual droplets within multi-droplet environments yet to be explored. Here, we present a fully automated, image-based, data-driven framework for analyzing corrosion progression under thousands of droplets simultaneously. Using time-resolved optical imaging and pre-trained large vision models for droplet segmentation, we construct per-droplet color features and propose a probability-based representation of corrosion product formation in inner and outer regions of interest. This approach overcomes the limitations of binary classification by capturing the continuous and spatially heterogeneous nature of corrosion product formation. Applied to carbon steel exposed to over 1500 pre-sprayed 1 M NaCl droplets of various sizes, the method reveals that the probability of corrosion product presence strongly depends on droplet size, with larger droplets more likely to exhibit products both under and around the droplet footprint. Moreover, corrosion products in the outer region can appear independently of under-droplet corrosion, suggesting a role for inter-droplet interactions. By transforming raw imaging data into physically meaningful per-droplet metrics, this work offers a scalable platform for investigating localized corrosion kinetics and morphology in complex, real-world droplet populations, opening new opportunities for connecting droplet formation and population behavior to local and overall atmospheric corrosion rates.

This study investigates time lags between environmental changes, electrolyte formation, and atmospheric corrosion sensor responses under controlled multi-droplet wetting. A commercial corrosion and environmental sensor was combined with in-situ microscopy, and an Artificial Intelligence (AI)-based segmentation approach was applied to track droplet growth. A cross-correlation analysis identified and quantified time lags between Surface Relative Humidity (SRH), droplet radius, and sensor responses based on Interdigitated Electrodes (IDE) measuring conductance, galvanic corrosion, and free corrosion. This approach ultimately aids in understanding how environmental fluctuations affect the dynamic behaviour of the electrolyte layer and, in turn, influence atmospheric corrosion sensor responses.

This paper presents a novel approach to investigate atmospheric corrosion kinetics of carbon steel under multi-droplet conditions. A homemade climate chamber has been developed to accurately control and monitor environmental conditions, including temperature (T) and relative humidity (RH), during exposure. Carbon steel corrosion kinetics are monitored with a custom-designed Electrical Resistance (ER) sensor pair. Savitzky-Golay (S-G) based filtering technique has been used for the corrosion signal processing. In parallel, top-view droplet temporal evolution has been recorded by microscopic imaging and analyzed for both droplet size distribution and the solid-liquid contact angle. The droplet size distribution can typically be described with a power-law form curve. The curve shows a decrease in height and a concurrent expansion in width with progressive drying. The introduction of NaCl into the electrolyte and surface roughness variations have also been identified to substantially influence the carbon steel corrosion rate. A strong correlation between the corrosion rate derived from the ER monitoring method and the RH can be observed. This correlation is further analyzed to incorporate the impact of droplet-based electrolyte conditions. This study offers valuable insights into the development of mechanistic and kinetic prediction models for atmospheric corrosion.

The authors regret that an error occurred in the description of equation 3 in the published version of the above-mentioned article, which should be as follows: [Formula presented] The correct equation was implemented for calculating all the results presented in the article, so all results, discussions and conclusions presented in the manuscript remain fully valid > The authors would like to apologise for any inconvenience caused.

Utilizing a dedicated micro-sized three-electrode cell, this study systematically investigates early-stage electrochemical properties and corrosion behavior of pure iron under single droplets. Various volumes and NaCl concentrations were considered during the evaporation-driven shape and concentration evolution of single droplets. The measurements disclosed that reducing the droplet size from 5 µL to 1.5 µL at 0.01 M NaCl concentration, increased noise resistance (R_n) and polarization resistance (R_p) values. However, at 0.1 M and 0.2 M NaCl concentrations, reducing droplet size led to the domination of relatively high chloride ion concentration over oxygen diffusion, resulting in a very low R_n and R_p and hence enhanced localized corrosion.