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Anti-freezing characteristics of water droplet impinging the superhydrophobic surface: An experimental and predictive study
[Display omitted] •Droplet impacting an inclined and supercooled superhydrophobic surface is studied.•A larger We number leads to a shift in the temperature limit of fully rebound to be higher.•As the inclined angle increases, both contact time and rebound height of droplet decreases.•The machine le...
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Published in: | Applied surface science 2021-11, Vol.566, p.150717, Article 150717 |
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container_title | Applied surface science |
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creator | Wang, Xin Tang, Zhiwen Xu, Bo Chen, Zhenqian |
description | [Display omitted]
•Droplet impacting an inclined and supercooled superhydrophobic surface is studied.•A larger We number leads to a shift in the temperature limit of fully rebound to be higher.•As the inclined angle increases, both contact time and rebound height of droplet decreases.•The machine learning model is first proposed to predict the rebound height of droplet.
Water freezing has a significant and non-negligible influence on the aircraft, power transmission lines and operational efficiency of industrial facilities. Therefore, it is of great value and meaning to deeply understand the dynamic behaviors of water droplet impacting the supercooled superhydrophobic surface. In this work, effects of impact velocity, surface temperature and inclined angle on the impinging droplet dynamics are visually investigated. The machine learning model is first proposed to predict the rebound height and temperature limit of fully rebound. The results demonstrate that a larger impact velocity shifts the temperature limit of completely rebound to a higher surface temperature. However, it has little effect on the spreading time and contact time. As the temperature further decreases, portion of droplet is pinned on the substrate instead of fully rebound and the volume of residual droplet increases. As the inclined angle increases, both contact time and rebound height decreases. Due to driven by the tangential component of gravity, width of droplet before detachment increases while the stretched length decreases. The optimal temperature limit of fully rebound is −35 °C with the inclined angle of 30° and We = 19, showing a significant improvement compared to the temperature limit on a horizontal surface. |
doi_str_mv | 10.1016/j.apsusc.2021.150717 |
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•Droplet impacting an inclined and supercooled superhydrophobic surface is studied.•A larger We number leads to a shift in the temperature limit of fully rebound to be higher.•As the inclined angle increases, both contact time and rebound height of droplet decreases.•The machine learning model is first proposed to predict the rebound height of droplet.
Water freezing has a significant and non-negligible influence on the aircraft, power transmission lines and operational efficiency of industrial facilities. Therefore, it is of great value and meaning to deeply understand the dynamic behaviors of water droplet impacting the supercooled superhydrophobic surface. In this work, effects of impact velocity, surface temperature and inclined angle on the impinging droplet dynamics are visually investigated. The machine learning model is first proposed to predict the rebound height and temperature limit of fully rebound. The results demonstrate that a larger impact velocity shifts the temperature limit of completely rebound to a higher surface temperature. However, it has little effect on the spreading time and contact time. As the temperature further decreases, portion of droplet is pinned on the substrate instead of fully rebound and the volume of residual droplet increases. As the inclined angle increases, both contact time and rebound height decreases. Due to driven by the tangential component of gravity, width of droplet before detachment increases while the stretched length decreases. The optimal temperature limit of fully rebound is −35 °C with the inclined angle of 30° and We = 19, showing a significant improvement compared to the temperature limit on a horizontal surface.</description><identifier>ISSN: 0169-4332</identifier><identifier>EISSN: 1873-5584</identifier><identifier>DOI: 10.1016/j.apsusc.2021.150717</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Anti-freezing ; Droplet impact ; Machine learning ; Superhydrophobic ; Temperature limit</subject><ispartof>Applied surface science, 2021-11, Vol.566, p.150717, Article 150717</ispartof><rights>2021 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c306t-433850b7ae1de4a9c969f7d595c5286dc44d6b04b8764d60573297fd0cb2e7133</citedby><cites>FETCH-LOGICAL-c306t-433850b7ae1de4a9c969f7d595c5286dc44d6b04b8764d60573297fd0cb2e7133</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Wang, Xin</creatorcontrib><creatorcontrib>Tang, Zhiwen</creatorcontrib><creatorcontrib>Xu, Bo</creatorcontrib><creatorcontrib>Chen, Zhenqian</creatorcontrib><title>Anti-freezing characteristics of water droplet impinging the superhydrophobic surface: An experimental and predictive study</title><title>Applied surface science</title><description>[Display omitted]
•Droplet impacting an inclined and supercooled superhydrophobic surface is studied.•A larger We number leads to a shift in the temperature limit of fully rebound to be higher.•As the inclined angle increases, both contact time and rebound height of droplet decreases.•The machine learning model is first proposed to predict the rebound height of droplet.
Water freezing has a significant and non-negligible influence on the aircraft, power transmission lines and operational efficiency of industrial facilities. Therefore, it is of great value and meaning to deeply understand the dynamic behaviors of water droplet impacting the supercooled superhydrophobic surface. In this work, effects of impact velocity, surface temperature and inclined angle on the impinging droplet dynamics are visually investigated. The machine learning model is first proposed to predict the rebound height and temperature limit of fully rebound. The results demonstrate that a larger impact velocity shifts the temperature limit of completely rebound to a higher surface temperature. However, it has little effect on the spreading time and contact time. As the temperature further decreases, portion of droplet is pinned on the substrate instead of fully rebound and the volume of residual droplet increases. As the inclined angle increases, both contact time and rebound height decreases. Due to driven by the tangential component of gravity, width of droplet before detachment increases while the stretched length decreases. The optimal temperature limit of fully rebound is −35 °C with the inclined angle of 30° and We = 19, showing a significant improvement compared to the temperature limit on a horizontal surface.</description><subject>Anti-freezing</subject><subject>Droplet impact</subject><subject>Machine learning</subject><subject>Superhydrophobic</subject><subject>Temperature limit</subject><issn>0169-4332</issn><issn>1873-5584</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9UMtOwzAQtBBIlMcfcPAPJNhJHCcckKqKl1SJC5wtZ70hrtokst1C4edxFM6c9jEzq9kh5IazlDNe3m5SPfq9hzRjGU-5YJLLE7LglcwTIarilCwirU6KPM_OyYX3G8Z4FtEF-Vn2wSatQ_y2_QeFTjsNAZ31wYKnQ0s_dRypccO4xUDtboy8iRo6pH4_ouuOE9gNjYW4cK0GvKPLnuJXBO0O-6C3VPeGjg6NhWAPURj25nhFzlq99Xj9Vy_J--PD2-o5Wb8-vayW6wRyVobJdSVYIzVyg4WuoS7rVhpRCxBZVRooClM2rGgqWcaOCZlntWwNgyZDyfP8khTzXXCD9w5bNUZf2h0VZ2oKUG3UHKCaAlRzgFF2P8swejtYdMqDxR7iEw4hKDPY_w_8Aj65fr4</recordid><startdate>20211115</startdate><enddate>20211115</enddate><creator>Wang, Xin</creator><creator>Tang, Zhiwen</creator><creator>Xu, Bo</creator><creator>Chen, Zhenqian</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20211115</creationdate><title>Anti-freezing characteristics of water droplet impinging the superhydrophobic surface: An experimental and predictive study</title><author>Wang, Xin ; Tang, Zhiwen ; Xu, Bo ; Chen, Zhenqian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c306t-433850b7ae1de4a9c969f7d595c5286dc44d6b04b8764d60573297fd0cb2e7133</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Anti-freezing</topic><topic>Droplet impact</topic><topic>Machine learning</topic><topic>Superhydrophobic</topic><topic>Temperature limit</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Xin</creatorcontrib><creatorcontrib>Tang, Zhiwen</creatorcontrib><creatorcontrib>Xu, Bo</creatorcontrib><creatorcontrib>Chen, Zhenqian</creatorcontrib><collection>CrossRef</collection><jtitle>Applied surface science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Xin</au><au>Tang, Zhiwen</au><au>Xu, Bo</au><au>Chen, Zhenqian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Anti-freezing characteristics of water droplet impinging the superhydrophobic surface: An experimental and predictive study</atitle><jtitle>Applied surface science</jtitle><date>2021-11-15</date><risdate>2021</risdate><volume>566</volume><spage>150717</spage><pages>150717-</pages><artnum>150717</artnum><issn>0169-4332</issn><eissn>1873-5584</eissn><abstract>[Display omitted]
•Droplet impacting an inclined and supercooled superhydrophobic surface is studied.•A larger We number leads to a shift in the temperature limit of fully rebound to be higher.•As the inclined angle increases, both contact time and rebound height of droplet decreases.•The machine learning model is first proposed to predict the rebound height of droplet.
Water freezing has a significant and non-negligible influence on the aircraft, power transmission lines and operational efficiency of industrial facilities. Therefore, it is of great value and meaning to deeply understand the dynamic behaviors of water droplet impacting the supercooled superhydrophobic surface. In this work, effects of impact velocity, surface temperature and inclined angle on the impinging droplet dynamics are visually investigated. The machine learning model is first proposed to predict the rebound height and temperature limit of fully rebound. The results demonstrate that a larger impact velocity shifts the temperature limit of completely rebound to a higher surface temperature. However, it has little effect on the spreading time and contact time. As the temperature further decreases, portion of droplet is pinned on the substrate instead of fully rebound and the volume of residual droplet increases. As the inclined angle increases, both contact time and rebound height decreases. Due to driven by the tangential component of gravity, width of droplet before detachment increases while the stretched length decreases. The optimal temperature limit of fully rebound is −35 °C with the inclined angle of 30° and We = 19, showing a significant improvement compared to the temperature limit on a horizontal surface.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.apsusc.2021.150717</doi></addata></record> |
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subjects | Anti-freezing Droplet impact Machine learning Superhydrophobic Temperature limit |
title | Anti-freezing characteristics of water droplet impinging the superhydrophobic surface: An experimental and predictive study |
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