Evidence map›Paper›PMID 33322682›Full record

ArticlePolymers2020

Functional Superhydrophobic Surfaces with Spatially Programmable Adhesion.

Duan-Yi Guo, Cheng-Huan Li, Li-Min Chang, Hung-Chang Jau, Wei-Chun Lo, Wei-Chun Lin, Chun-Ta Wang, Tsung-Hsien Lin

Abstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Duan-Yi GuoDepartment of Photonics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.
Cheng-Huan LiDepartment of Photonics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.
Li-Min ChangDepartment of Photonics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.
Hung-Chang JauDepartment of Photonics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.
Wei-Chun LoDepartment of Photonics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.
Wei-Chun LinDepartment of Photonics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.
Chun-Ta WangDepartment of Photonics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.
Tsung-Hsien LinDepartment of Photonics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.ORCID 0000-0003-0101-5637

Funding

Ministry of Science and Technology, Taiwan MOST 109-2112-M-110-013-MY3
6 · The paper itself

Abstract

A superhydrophobic surface that has controllable adhesion and is characterized by the lotus and petal effects is a powerful tool for the manipulation of liquid droplets. Such a surface has considerable potential in many domains, such as biomedicine, enhanced Raman scattering, and smart surfaces. There have been many attempts to fabricate superhydrophobic films; however, most of the fabricated films had uniform adhesion over their area. A patterned superhydrophobic surface with spatially controllable adhesion allows for increased functions in the context of droplet manipulation. In this study, we proposed a method based on liquid-crystal/polymer phase separation and local photopolymerization to realize a superhydrophobic surface with spatially varying adhesion. Materials and topographic structures were analyzed to understand their adhesion mechanisms. Two patterned surfaces with varying adhesion were fabricated from a superhydrophobic material to function as droplet guides and droplet collectors. Due to their easy fabrication and high functionality, superhydrophobic surfaces have high potential for being used in the fabrication of smart liquid-droplet-controlling surfaces for practical applications.

Indexed as

liquid crystallotus effectpetal effectphotopolymerizationssuperhydrophobic surfaces

Identifiers

PMID33322682
PMCPMC7763520

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.