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.

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.

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.

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.