Evidence map›Paper›PMID 38201767›Full record

ArticlePolymers2023

Enhancing the Toughness of PAA/LCNF/SA Hydrogel through Double-Network Crosslinking for Strain Sensor Application.

Xin Li, Hui Gao, Qiang Wang, Shanshan Liu

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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 at 1 institution in 1 country.

Xin LiState Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China.
Hui GaoState Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China.ORCID 0000-0002-3560-1055
Qiang WangState Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China.
Shanshan LiuState Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China.
Qilu University of Technology · CN

Funding

National Natural Science Foundation of China 32171714QUTJBZ Program of Qilu University of Technology (Shandong Academy of Sciences) 2022JBZ05Shandong Provincial Natural Science Foundation ZR2021QB102the Fundamental research projects for integrating science, education, and industry of Qilu University of Technology (Shandong Academy of Sciences) 2023PYI006 and 2023PX056the Outstanding Youth Innovation Team Project of Shandong Provincial University 2019KJC014the Talent Research Project of Qilu University of Technology (Shandong Academy of Sciences) 2023RCKY180
6 · The paper itself

Abstract

Lignin-containing nanocellulose fibers (LCNF) have been considered as a valuable enhancer for polyacrylic acid (PAA)-based hydrogels that can form rigid porous network structures and provide abundant polar groups. However, the PAA-LCNF hydrogel is dominated by a single-network (SN) structure, which shows certain limitations when encountering external environments with high loads and large deformations. In this paper, sodium alginate (SA) was introduced into the PAA-LCNF hydrogel network to prepare a double-network (DN) hydrogel structure of the SA-Ca

Indexed as

double-network hydrogelflexible sensorlignocellulose nanofibrilpolyacrylic acidsodium alginate

Identifiers

PMID38201767
PMCPMC10780929
OpenAlexW4390388726

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.