Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 528

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Skin‐Inspired Antibacterial Conductive Hydrogels for Epidermal Sensors and Diabetic Foot Wound Dressings

Zhao, Yue, Li, Zuhao, Song, Shanliang, Yang, Kerong, Liu, Hou, Yang, Zhe, Wang, Jincheng, Yang, Bai, Lin, Quan·2019·Advanced Functional Materials

Abstract

Recently, artificial intelligence research has driven the development of stretchable and flexible electronic systems. Conductive hydrogels are a class of soft electronic materials that have emerging applications in wearable and implantable biomedical devices. However, current conductive hydrogels possess fundamental limitations in terms of their antibacterial performance and a mechanical mismatch with human tissues, which severely limits their applications in biological interfaces. Here, inspired by animal skin, a conductive hydrogel is fabricated from a supramolecular assembly of polydopamine decorated silver nanoparticles (PDA@Ag NPs), polyaniline, and polyvinyl alcohol, namely PDA@Ag NPs/CPHs. The resultant hydrogel has many desirable features, such as tunable mechanical and electrochemical properties, eye‐catching processability, good self‐healing ability as well as repeatable adhesiveness. Remarkably, PDA@Ag NPs/CPHs exhibit broad antibacterial activity against Gram‐negative and Gram‐positive bacteria. The potential application of this versatile hydrogel is demonstrated by monitoring large‐scale movements of the human body in real time. In addition, PDA@Ag NPs/CPHs have a significant therapeutic effect on diabetic foot wounds by promoting angiogenesis, accelerating collagen deposition, inhibiting bacterial growth, and controlling wound infection. To the best of the authors' knowledge, this is the first time that conductive hydrogels with antibacterial ability are developed for use as epidermal sensors and diabetic foot wound dressing.

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 · 10.1002/adfm.201901474

Cites

35 of 35 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

Show all 35 references

Cited by

See all 528

Metadata

Authors
Zhao, Y., Li, Z., Song, S., Yang, K., Liu, H., Yang, Z., Wang, J., Yang, B., & Lin, Q.
Venue
Advanced Functional Materials
Publisher
Wiley
Published
2019-06-04
Volume
29
Issue
31
ISSN
  • 1616-301X (ISSN-L)
  • 1616-3028
OpenAlex
W2963872873
Cited by
528
References
35
FWCI
21.73
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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Skin‐Inspired Antibacterial Conductive Hydrogels for Epidermal Sensors and Diabetic Foot Wound Dressings. https://app.cochat.ai/papers/10.1002/adfm.201901474
The paper
Zhao, Y., Li, Z., Song, S., Yang, K., Liu, H., Yang, Z., Wang, J., Yang, B., & Lin, Q. (2019). Skin‐Inspired Antibacterial Conductive Hydrogels for Epidermal Sensors and Diabetic Foot Wound Dressings. Advanced Functional Materials. https://doi.org/10.1002/adfm.201901474

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.