Evidence map›Paper›PMID 37487078›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Water-assisted strong underwater adhesion via interfacial water removal and self-adaptive gelation.

Chenxi Qin, Yanfei Ma, Zhizhi Zhang, Yingjie Du, Sidi Duan, Shuanhong Ma, Xiaowei Pei, Bo Yu, Meirong Cai, Ximin He and 1 more

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
5.7field-weighted citation impact, top 3% of its field
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

6 citing papers in PubMed, 51 citations in OpenAlex.

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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

11 authors at 3 institutions in 2 countries.

Chenxi QinState Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.
Yanfei MaState Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.ORCID 0000-0001-5896-9461
Zhizhi ZhangState Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.
Yingjie DuDepartment of Materials Science and Engineering, University of California, Los Angeles, CA 90095.
Sidi DuanDepartment of Materials Science and Engineering, University of California, Los Angeles, CA 90095.
Shuanhong MaState Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.ORCID 0000-0002-2144-4378
Xiaowei PeiState Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.
Bo YuState Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.
Meirong CaiState Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.ORCID 0000-0002-2190-5541
Ximin HeDepartment of Materials Science and Engineering, University of California, Los Angeles, CA 90095.ORCID 0000-0001-8845-4637
Feng ZhouState Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.ORCID 0000-0001-7136-9233
Chinese Academy of Sciences · CNUniversity of California, Los Angeles · USYantai University · CN

Funding

MOST | National Key Research and Development Program of China (NKPs) 2021YFA0716304MOST | National Natural Science Foundation of China (NSFC) 22032006 22102201 22072169
6 · The paper itself

Abstract

In nearly all cases of underwater adhesion, water molecules typically act as a destroyer. Thus, removing interfacial water from the substrate surfaces is essential for forming super-strong underwater adhesion. However, current methods mainly rely on physical means to dislodge interfacial water, such as absorption, hydrophobic repulsion, or extrusion, which are inefficient in removing obstinate hydrated water at contact interface, resulting in poor adhesion. Herein, we present a unique means of reversing the role of water to assist in realizing a self-strengthening liquid underwater adhesive (SLU-adhesive) that can effectively remove water at contact interface. This is achieved through multiscale physical-chemical coupling methods across millimeter to molecular levels and self-adaptive strengthening of the cohesion during underwater operations. As a result, strong adhesion over 1,600 kPa (compared to ~100 to 1,000 kPa in current state of the art) can be achieved on various materials, including inorganic metal and organic plastic materials, without preloading in different environments such as pure water, a wide range of pH solutions (pH = 3 to 11), and seawater. Intriguingly, SLU-adhesive/photothermal nanoparticles (carbon nanotubes) hybrid materials can significantly reduce the time required for complete curing from 24 h to 40 min using near-infrared laser radiation due to unique thermal-response of the chemical reaction rate. The excellent adhesion property and self-adaptive adhesion procedure allow SLU-adhesive materials to demonstrate great potential for broad applications in underwater sand stabilization, underwater repair, and even adhesion failure detection as a self-reporting adhesive. This concept of "water helper" has potential to advance underwater adhesion and manufacturing strategies.

Indexed as

adhesivehydrated waterinterfacial waterself-adaptiveunderwater adhesion

Identifiers

PMID37487078
PMCPMC10400987
OpenAlexW4385191606

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.