Strong and highly conducting PPyNT/PAA/PVA triple network hydrogel: scalable construction and strain sensing

Strong and highly conducting hydrogel was prepared by introducing polypyrrole nanotubes into an ionically/covalently cross-linked PVA/PAA network, the composite hydrogel exhibits steady and sensitive strain sensing behaviours.

Authors

Institutions

Publication Details

Journal
Materials Chemistry Frontiers
Published
2025-01-01
DOI
https://doi.org/10.1039/d5qm00349k
Citations
1
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.67

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Strong and highly conducting PPyNT/PAA/PVA triple network hydrogel: scalable construction and strain sensing

Shi Wang, Boyuan Hu, Yong Wang, Huan Yang et al.
1 citations
Materials Chemistry Frontiers
Advanced Sensor and Energy Harvesting Materials
0.67
article

Strong and highly conducting PPyNT/PAA/PVA triple network hydrogel: scalable construction and strain sensing

Shi Wang, Boyuan Hu, Yong Wang, Huan Yang, Xingjian Xue, Xinli Jing, Yu Li, Yukai Chen, Peng Tian
article en
1 citations

Abstract

Strong and highly conducting hydrogel was prepared by introducing polypyrrole nanotubes into an ionically/covalently cross-linked PVA/PAA network, the composite hydrogel exhibits steady and sensitive strain sensing behaviours.

Materials Chemistry FrontiersVol. 9(17)
Xi'an Jiaotong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 29%
Advanced Sensor and Energy Harvesting Materials
0.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.