Strong Adhesives Mediated by Dynamic Phase-Locking.

Fanghao Dai, Wenhao Qi, Baohu Wu, Kai Liu, Peiyi Wu

Abstract read

In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 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

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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

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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

5 authors.

Fanghao DaiState Key Laboratory of Advanced Fiber Materials, Key Lab of Sustainable Low-Carbon Technologies for Textile Dyeing and Finishing, College of Chemistry and Chemical Engineering, Ministry of Education, Donghua University, Shanghai, China.

Wenhao QiState Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Baohu WuJülich Centre for Neutron Science (JCNS) At Heinz Maier-Leibnitz Zentrum (MLZ) Forschungszentrum Jülich, Garching, Germany.

Kai LiuState Key Laboratory of Advanced Fiber Materials, Key Lab of Sustainable Low-Carbon Technologies for Textile Dyeing and Finishing, College of Chemistry and Chemical Engineering, Ministry of Education, Donghua University, Shanghai, China.

Peiyi WuState Key Laboratory of Advanced Fiber Materials, Key Lab of Sustainable Low-Carbon Technologies for Textile Dyeing and Finishing, College of Chemistry and Chemical Engineering, Ministry of Education, Donghua University, Shanghai, China.ORCID https://orcid.org/0000-0001-7235-210X

Funding

Donghua University 2025 Cultivation Project of Discipline Innovation xkcx-202502National Natural Science Foundation of China 22575042National Natural Science Foundation of China 52433003

6 · The paper itself

Abstract

Nature has long inspired the design of reversible smart adhesives; however, achieving both high adhesion strength and switchability remains a significant challenge, particularly for emerging applications (e.g., soft robotics and wearable electronics). Herein, we introduce switchable phase-locking-mediated adhesives (SPAs) that leverage high-density hydrogen bonds to deliver ultrahigh adhesion (up to 15 MPa). The underlying mechanism involves dynamic phase-locking mediation that harmonizes interfacial adhesion with bulk cohesion through interfacial mechanical locking and strain-induced phase separation. This strategy optimizes performance across the complete adhesion lifecycle, including spreading, adhering, and debonding via temperature/force-mediated phase-locking. Through detailed molecular analysis of the SPA system, we uncover the mechanistic basis of ultrahigh adhesion and establish design guidelines applicable to future smart adhesive development.

Indexed as

hydrogen bondsphase‐lockingphase separationswitchable adhesivesultrahigh adhesion strength

Identifiers

PMID42400885

DOI10.1002/adma.73976

PMCPMC13486262

What OpenQuestion holds

Textmetadata

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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.