Evidence map›Paper›PMID 40708541›Full record

ArticleACS applied materials & interfaces2025

From Hydrophilic to Superhydrophobic: Tuning Surface Wettability through Salvinia-Inspired Topographies.

Kai Liu, Marco Sorgato, Enrico Savio

Abstract read
In one paragraph

Article in ACS applied materials & interfaces, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Kai LiuDepartment of Industrial Engineering, University of Padua, Via Venezia 1, Padova 35131, Italy.
Marco SorgatoDepartment of Industrial Engineering, University of Padua, Via Venezia 1, Padova 35131, Italy.ORCID 0000-0001-7293-0547
Enrico SavioDepartment of Industrial Engineering, University of Padua, Via Venezia 1, Padova 35131, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of superhydrophobic surfaces traditionally relies on combining surface roughness with low-surface-energy coatings. In contrast, this work demonstrates the use of two-photon polymerization to induce superhydrophobicity on hydrophilic substrates solely through structural design. A comprehensive set of Salvinia-inspired microstructures was fabricated with precise control over geometrical features such as the number of arms, arm diameter, fill configuration, spacing, and height. Static contact angle measurements revealed that surface architecture plays a pivotal role in modulating wettability, with optimized structures achieving contact angles above 160° without any chemical modification. The study further investigates how morphological fidelity, governed by two-photon polymerization (TPP) printing parameters─specifically slicing distance and hatching distance─influences surface quality, roughness, and droplet behavior. Power spectral density analysis and 3D surface topography confirm that fabrication resolution critically impacts the performance of designed features. Finally, fabrication efficiency was evaluated in terms of areal fabrication rate, highlighting trade-offs among design complexity, printing resolution, and throughput. The results establish a set of design principles for achieving superhydrophobicity on hydrophilic materials and provide a scalable framework for future applications in microfluidics, biomimetics, and surface engineering where chemical-free wettability control is desired.

Indexed as

3D structuresbioinspiredsuperhydrophobicsurface designsurface functionalizationtwo photon polymerization

Identifiers

PMID40708541
PMCPMC12332838

What OpenQuestion holds

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Registered trials

None linked

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.