Evidence map›Paper›PMID 41766618›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Harnessing Phase Separation for the Development of High-Performance Hydrogels.

Yue Shao, Yiming Ma, Baihao Shao, Molly M Stevens

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. 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

4 authors.

Yue ShaoDepartment of Physiology, Anatomy and Genetics, Department of Engineering Science, and Kavli Institute for Nanoscience Discovery, University of Oxford, Oxford, UK.ORCID https://orcid.org/0009-0009-6874-929X
Yiming MaDepartment of Physiology, Anatomy and Genetics, Department of Engineering Science, and Kavli Institute for Nanoscience Discovery, University of Oxford, Oxford, UK.
Baihao ShaoDepartment of Physiology, Anatomy and Genetics, Department of Engineering Science, and Kavli Institute for Nanoscience Discovery, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0003-0072-2946
Molly M StevensDepartment of Physiology, Anatomy and Genetics, Department of Engineering Science, and Kavli Institute for Nanoscience Discovery, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-7335-266X

Funding

CUHK's Vice-Chancellor Early Career Professorship SchemeDepartment of Science, Innovation and TechnologyEngineering and Physical Sciences Research Council EP/P001114/1Engineering and Physical Sciences Research Council EP/T020792/1Natural Sciences and Engineering Research Council of CanadaRosetrees TrustRoyal Academy of Engineering CiET2021∖94UK Research and Innovation Postdoctoral Fellowship EP/X027252/1University of Oxford Strategic Research Fund
6 · The paper itself

Abstract

Hydrogels are indispensable for the development of next-generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by more than just covalent bonds and polymer entanglements. By regulating the demixing of polymer-rich and solvent-rich domains, phase separation leads to architectures that couple strength, elasticity, and dynamic responsiveness. This article reviews the recent advances in designing high-performance phase-separated hydrogels by linking phase separation behavior within polymer networks to emergent properties such as toughness, fatigue resistance, adhesion, and stimuli-responsiveness. We highlight how mesoscale organization governs multifunctional performance and demonstrate how these principles help resolve the key trade-offs in critical applications, such as high-pressure hemostatic sealants, low-impedance bioelectronics, perfusable tissue engineering scaffolds, and adaptive soft robotics. Finally, we discuss critical challenges, including in situ characterization and scalability, and future opportunities like machine-learning-guided design, which are essential to translate phase separation from a materials heuristic into design rules for reliable, high-performance hydrogel materials.

Indexed as

hydrogelphase separationpolymersoft roboticswearable sensors

Identifiers

PMID41766618
PMCPMC13325843

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.