Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 443

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Recent Advancements in Flexible and Stretchable Electrodes for Electromechanical Sensors: Strategies, Materials, and Features

Zhao, Songfang, Li, Jinhui, Cao, Duxia, Zhang, Guoping, Li, Jia, Li, Kui, Yang, Yang, Wang, Wei, Jin, Yufeng, Sun, Rong, Wong, Ching-Ping·2017·ACS Applied Materials & Interfaces

Abstract

Stretchable and flexible sensors attached onto the surface of the human body can perceive external stimuli, thus attracting extensive attention due to their lightweight, low modulus, low cost, high flexibility, and stretchability. Recently, a myriad of efforts have been devoted to improving the performance and functionality of wearable sensors. Herein, this review focuses on recent remarkable advancements in the development of flexible and stretchable sensors. Multifunction of these wearable sensors is realized by incorporating some desired features (e.g., self-healing, self-powering, linearity, and printing). Next, focusing on the characteristics of carbon nanomaterials, nanostructured metal, conductive polymer, or their hybrid composites, two major strategies (e.g., materials that stretch and structures that stretch) and diverse design approaches have been developed to achieve highly flexible and stretchable electrodes. Strain sensing performances of recently reported sensors indicate that the appropriate choice of geometric engineering as well as intrinsically stretchable materials is essential for high-performance strain sensing. Finally, some important directions and challenges of a fully sensor-integrated wearable platform are proposed to realize their potential applications for human motion monitoring and human-machine interfaces.

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.6b13800

Cites

20 of 20 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 443

Metadata

Authors
Zhao, S., Li, J., Cao, D., Zhang, G., Li, J., Li, K., Yang, Y., Wang, W., Jin, Y., Sun, R., & Wong, C.-P.
Venue
ACS Applied Materials & Interfaces
Published
2017-03-30
Volume
9
Issue
14
Pages
12147-12164
ISSN
  • 1944-8244 (ISSN-L)
  • 1944-8252
OpenAlex
W2592124801
Cited by
443
References
20
FWCI
23.98
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.