20.500.12556/RUL-169589 Dataset on droplet spreading and rebound behavior of water and viscous water-glycerol mixtures on superhydrophobic surfaces with laser-made channels Droplet impact, spreading and rebound was investigated experimentally on superhydrophobic laser-textured surfaces, yielding a dataset of 1498 datapoints. Data was collected on twelve types of surfaces with square grids of laser-made channels of various spacings (from 50 µm to 800 µm), with two groups of six surfaces possessing either deep or shallow laser-made channels. Droplet impact tests were performed with water and viscous water-glycerol mixtures with viscosity values up to 160 mPa·s and droplet impact behavior was images with a high-speed camera at 5000 fps. Maximum spreading factor, contact time, droplet rebound efficiency, and maximum lamella velocity were extracted from the videos using software image processing. Moreover, information on droplet diameter, velocity, density, surface tension, dynamic viscosity, Weber number, and Reynolds number are provided. A supplementary dataset includes the same quantitative information for droplet impacts on a smooth, hydrophobic surface, resembling the surface between the laser-made channels on other superhydrophobic surfaces (125 additional datapoints). Furthermore, scanning electron microscopy images of the surfaces are provided alongside the measurements of static and dynamic contact angles with water and water-glycerol mixtures. The data may be useful for fields like wettability studies, surface engineering, and anti-icing research. It can help validate theoretical and numerical models of droplet spreading, retracting, and rebounding from poorly wettable surfaces, optimize superhydrophobic surfaces for applications such as self-cleaning and drag reduction, and contribute to machine learning models predicting droplet behavior. The data is particularly relevant for designing anti-icing surfaces by minimizing contact time and maximizing the restitution coefficient. Additionally, it supports applications in 3D printing, coating technologies, and inkjet printing by providing data on viscous liquid impacts on poorly wettable surfaces. droplet impact droplet-surface interaction nonwetting surfaces laser-textured surfaces superhydrophobic surfaces self-cleaning surfaces padec kapljice interakcija kapljice s površino neomočljive površine lasersko strukturirane površine superhidrofobne površine samočistilne površine true false true Angleški jezik Slovenski jezik Članek v reviji 2025-06-05 10:18:32 2025-06-05 10:18:53 2025-06-06 04:42:47 0000-00-00 00:00:00 2025 0 0 10 str. art. 111697 Vol. 61 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 532 2352-3409 10.1016/j.dib.2025.111697 238364931 https://www.sciencedirect.com/science/article/pii/S2352340925004275 1 69050634-41e4-11f0-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=211077 RAZ_Moze_Matic_2025.pdf RAZ_Moze_Matic_2025.pdf 1 23A53774BED6B7957D663E956C055BFA e229a49b3637cab3664761b5e44c4165479bf4f986c5a51cd497e594aeb2109f 6581c4e2-41e5-11f0-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=211081 Fakulteta za strojništvo 0 0 0