Evidence map›Paper›PMID 28461887›Full record

ArticleJournal of materials chemistry. B2016

Recovery property of double-network hydrogel containing mussel-inspired adhesive moiety and nano-silicate.

Yuan Liu, Bruce P Lee

Abstract read
In one paragraph

Article in Journal of materials chemistry. B, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 41 citations in OpenAlex.

  1. pH Responsive Antibacterial Hydrogel Utilizing Catechol-Boronate Complexation Chemistry.Chemical engineering journal (Lausanne, Switzerland : 1996) · 2022
    Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. Multifunctional Biomedical Adhesives.Advanced healthcare materials · 2019
    Review
  7. Article
  8. Article
  9. 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

2 authors at 1 institution in 1 country.

Yuan LiuDepartment of Biomedical Engineering, Michigan Technological University, 1400 Townsend Dr, Houghton, MI, 49931, USA.
Bruce P LeeDepartment of Biomedical Engineering, Michigan Technological University, 1400 Townsend Dr, Houghton, MI, 49931, USA.
Houghton University · US

Funding

Biomimetic Tissue Adhesive with Mechanically Tough Hydrogel SupportR15GM104846 · NIGMS · MICHIGAN TECHNOLOGICAL UNIVERSITY · PI LEE, BRUCE P · 2013 to 2016
$757k
NIGMS NIH HHS R15 GM104846
6 · The paper itself

Abstract

Altough double network (DN) hydrogels are extremly tough, they are irreversibly softened during large strain deformation. We incorporated mussel-inspired adhesive moiety, catechol, and a synthetic nano-silicate, Laponite, into DN to examine the effect of strong, reversible crosslinks on the DN's ability to recover its mechanical properties during successive loading cycles. The introduction of catechol and Laponite drastically increased the compressive strength and toughness of DN without compromising the compliance of the hydrogel. After 2 hours of recovery at room temperature, the nanocomposite DN hydrogel recovered over 95 and 82 % of its strain energy and hysteresis, respectively, during successive compressive loading to a strain of 0.5. Both equilibrium swelling and oscillatory rheometry data confirmed that there were minimal changes to the network crosslinking density and stiffness after large strain compressive deformation, indicating that mechanical loading did not result in irreversible structural damage. Strong catechol-Laponite interactions can be repeatedly broken and reform to dissipate fracture energy and enable the recovery of DN hydrogel.

Identifiers

PMID28461887
PMCPMC5409110
OpenAlexW2520148676

What OpenQuestion holds

Textmetadata
LicenceTDM
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.