Abstract
Nanobubbles (NBs) on hydrophobic surfaces in aqueous solvents have shown great potential in numerous applications. In this study, the morphological characterization of NBs in AFM images was carried out with the assistance of a novel image segmentation method. The method combines the classical threshold method and a modified, active contour method to achieve optimized image segmentation. The image segmentation results obtained with the classical threshold method and the proposed, modified method were compared. With the modified method, the diameter, contact angle, and radius of curvature were automatically measured for all NBs in AFM images. The influence of the selection of the threshold value on the segmentation result was discussed. Moreover, the morphological change in the NBs was studied in terms of density, covered area, and volume occurring during coalescence under external disturbance.
Highlights
Over the last ten years, spherical-capped bubbles on various hydrophobic surfaces in aqueous solvents have gained increasing attention [1,2,3,4,5].These gas bubbles with dimensions of 5–100 nm in height and 100–800 nm in diameter are often referred to as nanobubbles (NBs)
We provide a systematic approach for NB morphological characterization
The morphological characterization for the NBs found in the atomic force microscopy (AFM) image was automatically implemented and the NB boundaries were detected
Summary
Over the last ten years, spherical-capped bubbles on various hydrophobic surfaces in aqueous solvents have gained increasing attention [1,2,3,4,5].These gas bubbles with dimensions of 5–100 nm in height and 100–800 nm in diameter are often referred to as nanobubbles (NBs). The NB properties, including diameter, height, contact angle, radius of curvature, density and covered area, are normally studied through morphological characterization from AFM images.
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