Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 302

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

Maximizing the Giant Liquid Slip on Superhydrophobic Microstructures by Nanostructuring Their Sidewalls

Lee, Choongyeop, Kim, Chang-Jin “CJ”·2009·Langmuir

Abstract

In an effort to maximize the liquid slip on superhydrophobic surfaces, we investigate the role of the nanoscale roughness on microscale structures by developing well-defined micro-nano hierarchical structures. The nonwetting stability and slip length on the dual-scale micro-nano structures are measured and compared with those on single-scale micro-smooth structures. A force balance between a liquid pressure and a surface tension indicates that hydrophobic nanostructures on the sidewall of microposts or microgrates would expand the range of the nonwetted state. When a higher gas fraction or a larger pitch can be tested without wetting, a larger slip length is expected on the microstructures. An ideal dual-scale structure is described that isolates the role of the nanostructures, and a fabrication technique is developed to achieve such a microstructure-smooth tops and nanostructured sidewalls. The tests confirm such micro-nano structures allow a nonwetted state at a higher gas fraction or a larger pitch than the previous micro-smooth structures. As a result, we achieve the maximum slip length of approximately 400 microm on the dual-scale structures, an increase of approximately 100% over the previous maximum reported on the single-scale (i.e., micro-smooth) structures. The study ameliorates our understanding of the role of each scale on hierarchical structures for a wetting transition and a liquid slip. The resulting giant slip is large enough to influence many fluidic applications, even in macroscale.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/la901824d

Cites

19 of 19 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 19 references

Cited by

Metadata

Authors
Lee, C., & Kim, C.-J. “.
Venue
Langmuir
Published
2009-07-17
Volume
25
Issue
21
Pages
12812-12818
ISSN
  • 0743-7463 (ISSN-L)
  • 1520-5827
OpenAlex
W1990337245
Cited by
302
References
19
FWCI
8.02
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.