Introduction Condensation and freezing of water droplets on solid surfaces occur in a wide range of natural and engineered systems; uncontrolled or unwanted ice formation poses significant challenges to performance and safety. Surface texture greatly influences droplet nucleation, growth, coalescence, and freezing mechanisms by affecting wettability and droplet pinning. Method In this paper, the effects of a microtextured aluminum surface are visualized at high magnification (e.g., 600×) during condensation from moist air at 20 °C–23 °C and 39%–47% RH. Condensed droplet images are processed with an artificial intelligence (AI) model. Results and discussion Different textures measurably affect droplet condensation dynamics and subsequent freezing behavior. A neural network-based object detection model was developed to quantify droplet population, average diameter, phase state, and surface coverage across entire fields of view. The model was trained on over 1,300 images. The detection model provided statistically robust insights into the relationships of condensation dynamics, surface texture, and freezing behavior. The AI-derived measurements for condensed droplets show that both droplet population decline and diameter growth follow power-law scaling over time. The microtextured surface displayed smaller power-law exponents compared to the smooth control surface. This indicates a shift in condensation behavior caused by increased droplet pinning and decreased mobility on the microtextured surface. These changes are also linked to much faster freezing. The microtextured surfaces achieved full frost coverage at an average time of 139.5 s, which is roughly three times quicker than smooth substrates with an average freezing time of 419.5 s. The findings reveal that surface-induced pinning directly influenced condensation growth and subsequent freezing behavior.
Turner et al. (Wed,) studied this question.