4.8 Article

Superhydrophobic Surface Designing for Efficient Atmospheric Water Harvesting Aided by Intelligent Computer Vision

期刊

ACS APPLIED MATERIALS & INTERFACES
卷 15, 期 21, 页码 25849-25859

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsami.3c03436

关键词

atmospheric water harvesting; superhydrophobic; microflower; hierarchical structure; dropwise condensation

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Atmospheric water harvesting (AWH) is a possible solution for the water crisis and the key process has been applied in commercial dehumidifiers. A superhydrophobic surface technique, induced by coalescence-induced jumping, is proposed to enhance the AWH process. In this study, a simple and low-cost approach for superhydrophobic surface engineering through alkaline oxidation of copper is reported, which provides medium-sized microflower structures that act as nucleation sites and promoters for the AWH process. Machine learning computer vision techniques are also applied to optimize the AWH structure for droplet dynamic analysis on a micrometer scale. Overall, the alkaline surface oxidation and medium-scale microstructures offer great opportunities for superhydrophobic surfaces in AWH applications.
Atmospheric water harvesting (AWH) is a possible solutionfor thecurrent water crisis on the Earth, and the key process of AWH hasbeen widely applied in commercial dehumidifiers. To improve the energyefficiency of the AWH process, applying a superhydrophobic surfaceto trigger coalescence-induced jumping could be a promising techniquethat has attracted extensive interest. While most previous studiesfocused on optimizing the geometric parameters such as nanoscale surfaceroughness (<1 mu m) or microscale structures (10 mu m toa few hundred mu m range), which might enhance AWH, here, we reporta simple and low-cost approach for superhydrophobic surface engineering,through alkaline oxidation of copper. The prepared medium-sized microflowerstructures (3-5 mu m) by our method could fill the gapof the conventional nano- and microstructures, simultaneously actas the preferable nucleation sites and the promoter for the condenseddroplet mobility including droplet coalescence and departure, andeventually benefit the entire AWH performances. Moreover, our AWHstructure has been optimized with the aid of machine learning computervision techniques for droplet dynamic analysis on a micrometer scale.Overall, the alkaline surface oxidation and medium-scale microstructurescould provide excellent opportunities for superhydrophobic surfacesfor future AWH.

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