Measurements of copper droplet oscillations on tungsten substrate and the angular dependence of the oscillation frequency

The study of droplet impingement and subsequent oscillations on solid substrates is critical for understanding wetting dynamics and heat transfer in applications such as spray cooling and metal coating. However, existing experimental approaches often rely on low-speed imaging or manual analysis, which limits their ability to capture rapid, transient oscillations and achieve high precision, particularly under extreme high-temperature and vacuum conditions. Moreover, conventional methods face challenges in automatically extracting key dynamic parameters like contact spot diameter and oscillation frequencies without user intervention. Novel methods for the computer processing of high-speed video images from experiments on droplet impingement and subsequent oscillations on a solid substrate were developed and validated. The image analysis algorithms, implemented in the Python programming language utilizing the OpenCV computer vision library, enable automated, high-precision tracking of dynamic droplet parameters. These methods were successfully applied to real high-temperature experiments involving molten copper droplets falling onto a polished tungsten substrate under vacuum conditions. Through automated image processing, time-dependent evolutions of the droplet center-of-mass coordinates, the diameter of the contact spot with the solid surface, and the dynamic contact wetting angles for the Cu/W system were obtained. The analysis reveals that upon impact, the droplet undergoes damped shape oscillations. The fundamental oscillation frequencies of the droplets and their dependence on mass were determined with high accuracy. Furthermore, by integrating data from other experimental systems, a generalized angular dependence of the oscillation frequency for sessile droplets was established and compared with existing theoretical models.