4.7 Article

Bioinspired superhydrophilic-hydrophobic integrated surface with conical pattern-shape for self-driven fog collection

期刊

JOURNAL OF COLLOID AND INTERFACE SCIENCE
卷 530, 期 -, 页码 274-281

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcis.2018.06.081

关键词

Bioinspired; Superhydrophilic; Conical surface; Self-driven; Fog collection

资金

  1. National Science Foundation of China [51661145024, 21374116]
  2. Scientific Development Program of Jilin Province [20160519006JH]
  3. Chinese Academy of Sciences-Wego Group High-tech Research & Development Program
  4. Primary Research and Development Program of Shandong Province [2017GGX202002]
  5. SDUT&Zibo City Integration Development Project [2017ZBXC206]

向作者/读者索取更多资源

It is well recognized by the scientific community that the fog can be deposited and transported on asymmetric surfaces, thus numerous efforts have been made to create such surfaces. However, it is still challenging to design a surface capable of fast deposition and rapid transportation simultaneously. Herein, inspired by the asymmetric structure of cactus spines and the cooperative hydrophilic/hydrophobic regions of desert beetles, a superhydrophilic-hydrophobic integrated conical stainless steel needle (SHCSN) is fabricated by a facile method. This integrated needle surface combines the merits of the fast deposition of fog on hydrophobic region and then rapid transportation on superhydrophilic surface. The droplet average transportation velocity on SHCSN is greater than other types of surfaces because of large Laplace pressure and self-driven phenomenon at its superhydrophilic-hydrophobic boundary. The best fog harvest efficiency was realized by optimizing the length of the hydrophobic region using theoretical modeling and experimental exploration, whereas the robust superhydrophilic needle surface induced the increase of collection time. This SHCSN was realized to be more efficient in fog collection than uniform superhydrophilic, uniform hydrophobic/superhydrophobic needle surfaces. (C) 2018 Elsevier Inc. All rights reserved.

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