Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 267

The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.

Conductive and Tough Hydrogels Based on Biopolymer Molecular Templates for Controlling in Situ Formation of Polypyrrole Nanorods

Gan, Donglin, Han, Lu, Wang, Menghao, Xing, Wensi, Xu, Tong, Zhang, Hongping, Wang, Kefeng, Fang, Liming, Lu, Xiong·2018·ACS Applied Materials & Interfaces

Abstract

Conductive hydrogels (CHs) have gained significant attention for their wide applications in biomedical engineering owing to their structural similarity to soft tissues. However, designing CHs that combine biocompatibility with good mechanical and electrical properties is still challenging. Herein, we report a new strategy for the fabrication of tough CHs with excellent conductivity, superior mechanical properties, and good biocompatibility by using chitosan framework as molecular templates for controlling conducting polypyrrole (PPy) nanorods in situ formation inside the hydrogel networks. First, polyacrylamide/chitosan (CS) interpenetrating polymer network hydrogel was synthesized by UV photopolymerization; second, hydrophobic and conductive pyrrole monomers were absorbed and fixed on CS molecular templates and then polymerized with FeCl 3 in situ inner hydrophilic hydrogel network. This strategy ensured that the hydrophobic PPy nanorods were uniformly distributed and integrated with the hydrophilic polymer phase to form highly interconnected conductive path in the hydrogel, endowing the hydrogel with high conductivity (0.3 S/m). The CHs exhibited remarkable mechanical properties after the chelation of CS by Fe 3+ and the formation of composites with the PPy nanorods (fracture energy 12 000 J m –2 and compression modulus 136.3 MPa). The use of a biopolymer molecular template to induce the formation of PPy nanostructures is an efficient strategy to achieve conductive multifunctional hydrogels.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acsami.8b10280

Cites

57 of 57 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 267

Metadata

Authors
Gan, D., Han, L., Wang, M., Xing, W., Xu, T., Zhang, H., Wang, K., Fang, L., & Lu, X.
Venue
ACS Applied Materials & Interfaces
Published
2018-09-25
Volume
10
Issue
42
Pages
36218-36228
ISSN
  • 1944-8244 (ISSN-L)
  • 1944-8252
OpenAlex
W2892572292
Cited by
267
References
57
FWCI
11.31
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.