Evidence map›Paper›PMID 41228643›Full record

ArticlePolymers2025

Impact of Silica Nanoparticles on Mechanical Properties and Self-Healing Performance of PVA Hydrogels.

Moustapha Mohamed Mahamoud, Yutaka Kuwahara, Hirotaka Ihara, Makoto Takafuji

Abstract read
In one paragraph

Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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.

Moustapha Mohamed MahamoudFaculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan.ORCID 0009-0009-4167-6369
Yutaka KuwaharaFaculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan.ORCID 0000-0003-2554-6993
Hirotaka IharaFaculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan.ORCID 0000-0002-3642-8637
Makoto TakafujiFaculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan.ORCID 0000-0001-9985-2569

Funding

Japan International Cooperation Agency SDGs global leader program
6 · The paper itself

Abstract

Hydrogels are three-dimensional polymeric networks capable of retaining large amounts of water. Polyvinyl alcohol (PVA)-based hydrogels exhibit autonomous self-healing through reversible physical interactions within the hydrogel matrix, including hydrogen bonding, crystallite formation, and dynamic crosslinking. However, their long self-healing times and low strength limit practical application. Herein, we propose an effective strategy to simultaneously achieve excellent self-repairing and high mechanical strength. The tensile strength of uncut PVA hydrogel was 1.21 MPa; after cutting and rejoining for 12 h at room temperature (RT), it recovered 94% of the original uncut strength. To accelerate self-healing, hydrogels were treated at 40, 50, and 60 °C for 20, 40, and 60 min. Under optimal conditions (60 °C for 60 min), 96% recovery was achieved. Mechanical properties were further improved by silica (Si) nanoparticles of various sizes (~12, ~85, and ~200 nm). Si-loaded hydrogels, particularly ~12 nm, demonstrated increased mechanical properties, reaching a tensile strength of 1.45 MPa and a self-healing recovery of 95% of the uncut hydrogel strength. Ultra-small (~12 nm) Si nanoparticles enhanced the overall mechanical properties by acting as an efficient nucleating agent and did not hinder the existing self-healing mechanism. The developed strategy will pave the way for novel techniques in hydrogel research and will advance applications such as soft robotics and wound dressing.

Indexed as

hydrogelspolyvinyl alcoholself-healingsilica nanoparticles

Identifiers

PMID41228643
PMCPMC12610640

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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.