Daniel Dan, Koh Xue Qi
Division of Physical Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
Institute of Materials Research and Engineering, Agency for Science, Technology and Research (A*STAR), 138634, Singapore.
Soft Matter. 2023 Nov 8;19(43):8434-8439. doi: 10.1039/d3sm01178j.
Droplets adhere to surfaces due to their surface tension and understanding the vertical force required to detach the droplet is key to many technologies (, inkjet printing, optimal paint formulations). Here, we predicted on different surfaces by numerically solving the Young-Laplace equation. Our numerical results are consistent with previously reported results for a wide range of experimental conditions: droplets subjected to surface body forces with || ranging from nano- to milli-newtons, droplet radii ranging from tens of microns to several millimetres, and for various surfaces (micro-/nano-structured superhydrophobic lubricated surfaces). Finally, we derive an analytic solution for on highly hydrophobic surfaces and further show that for receding contact angle > 140°, the normalized /π is equivalent to the Young-Dupre work of adhesion (1 + cos ).
由于表面张力,液滴会附着在表面上,而了解分离液滴所需的垂直力是许多技术(如喷墨打印、优化涂料配方)的关键。在此,我们通过数值求解杨-拉普拉斯方程,预测了不同表面上的情况。我们的数值结果与先前报道的在广泛实验条件下的结果一致:液滴受到大小从纳牛到毫牛的表面体力作用,液滴半径从几十微米到几毫米不等,且适用于各种表面(微/纳米结构超疏水表面、润滑表面)。最后,我们推导出了高疏水表面上的解析解,并进一步表明,对于后退接触角大于140°的情况,归一化的/π等于杨氏-杜普雷粘附功(1 + cos )。