The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Femtosecond Laser Weaving Superhydrophobic Patterned PDMS Surfaces with Tunable Adhesion
Abstract
We present a rapid, facile, and simple method to realize superhydrophobic patterned polydimethylsiloxane (PDMS) surfaces with tunable adhesion by a femtosecond laser. These surfaces are composed of superhydrophobic laser-induced structures and hydrophobic unstructured square array. The femtosecond laser structured domain shows superhydrophobicity with ultralow water adhesion, while the nonstructured flat PDMS shows ordinary hydrophobicity with ultrahigh water adhesion. By adjusting the relative area fraction of laser structured and nonstructured domains, the as-prepared superhydrophobic surfaces show tunable water adhesion that ranges from ultralow to ultrahigh, on which the sliding angle can be controlled from 1° to 90° (a water droplet cannot slide down even when the as-prepared surface is vertical or turned upside down). The tunable adhesive superhydrophobic surfaces achieved by femtosecond laser microfabrication may be potentially used in microfluidic systems to modulate the mobility of liquid droplets.
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Citations
Cites
Wettability of porous surfaces
Cassie, A. B. D., & Baxter, S. (1944) · Transactions of the Faraday Society · doi:10.1039/tf9444000546 · Cited by 13,807
Cited by
Superhydrophobic Surfaces: Insights from Theory and Experiment
Parvate, S., Dixit, P., & Chattopadhyay, S. (2020) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.9b08567 · Cited by 787
Metadata
- Authors
- Yong, J., Chen, F., Yang, Q., Zhang, D., Du, G., Si, J., Yun, F., & Hou, X.
- Venue
- The Journal of Physical Chemistry C
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-11-15
- Volume
- 117
- Issue
- 47
- Pages
- 24907-24912
- ISSN
- 1932-7447 (ISSN-L)
- 1932-7455
- OpenAlex
- W2316907077
- Cited by
- 165
- References
- 1
- FWCI
- 4.60
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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