Evidence map›Paper›PMID 42162417›Full record

ReviewNano-micro letters2026

Biomimetic Multi-Responsive Superwettable Materials for Oil-Water Separation.

Chengkang Rao, Yan Xin, Zhiguang Guo, Weimin Liu

Abstract readReview
In one paragraph

Review in Nano-micro letters, 2026. 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

4 authors.

Chengkang RaoMinistry of Education Key Laboratory for the Green Preparation and Application of Functional Materials, Hubei University, Wuhan, 430062, People's Republic of China.
Yan XinMinistry of Education Key Laboratory for the Green Preparation and Application of Functional Materials, Hubei University, Wuhan, 430062, People's Republic of China. 42952609@qq.com.
Zhiguang GuoMinistry of Education Key Laboratory for the Green Preparation and Application of Functional Materials, Hubei University, Wuhan, 430062, People's Republic of China. zguo@licp.cas.cn.
Weimin LiuState Key Laboratory of Silicate Materials for Architectures and School of Materials Science and Engineering, Wuhan University of Technology, Wuhan, 430070, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Industrial oily wastewater discharges and marine oil spills pose a serious threat to ecosystems. A new strategy for efficient and controllable oil-water separation is provided by smart-responsive wettability materials, owing to their ability to dynamically switch surface wettability in response to external stimuli. Under this premise, we reviewed the research progress and applications of such materials. First, we described the theoretical basis of wettability and the mechanism of oil-water separation. Subsequently, we comparatively analyzed the structural characteristics and separation properties of four types of special wettable materials. We focused on eight categories of smart response wetting materials: temperature, pH, light, electricity, gas, ion, solvent, and multi-response. For each type, we analyzed the response mechanisms, advantages, and limitations in oil-water separation. In addition, we compared the advantages and disadvantages of key preparation techniques such as layer-by-layer self-assembly, electrostatic spinning, and surface-initiated atom transfer radical polymerization. Finally, we summarized the current research status and challenges in the field of smart-responsive wetting materials and looked forward to future development directions.

Indexed as

Oil–water separationPreparationSmart response materialsWettability

Identifiers

PMID42162417
PMCPMC13190935

What OpenQuestion holds

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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.