Recyclable Ionogel with Shape Memory‐Assisted Healing Microstructure for Highly Sensitive Ionotronic Pressure Sensor

Surface microstructures have been widely employed in pressure sensors to enhance sensitivity. However, the microstructures are susceptible to irreversible collapse under prolonged cyclic loading, leading to device failure. This work develops a recyclable ionogel (PUF/IL) with shape memory-assisted healing microstructure for highly sensitive ionotronic pressure sensor. Hydrogen bond units (UPy) and fluorinated chain extenders (OHD) are used to regulate the various properties of PUF/IL. Benefiting from the ion-dipole interactions between OHD and ionic liquids (IL), IL can be firmly stabilized in the ionogel network. PUF/IL exhibits exceptional shape-memory properties, demonstrating fixation and recovery rates of 99% and 86%, respectively. More importantly, when the microstructure is mechanically damaged during long-term use, it can be fully recovered through a shape-memory process. Due to the dynamic interactions, PUF/IL shows remarkable recyclability. The mechanical properties, shape memory performance, and pressure-sensing capabilities of recycled PUF/IL retain over 95% of their initial values. Overall, the strategy of healing collapsed microstructures via the shape-memory effect of PUF/IL, combined with its recyclability, effectively improves the long-term reliability and sustainability of pressure sensors. This work provides a solid foundation and creative design ideas for the development of next-generation durable, sustainable, highly sensitive pressure sensors.

Authors

Institutions

Publication Details

Journal
Small
Published
2026-01-05
DOI
https://doi.org/10.1002/smll.202512853
Citations
1
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
21.28

Funders

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

Recyclable Ionogel with Shape Memory‐Assisted Healing Microstructure for Highly Sensitive Ionotronic Pressure Sensor

Lianghao Jia, Yong Zhang, Zhengen Wei, Tao Xiang et al.
1 citations
Small
Advanced Sensor and Energy Harvesting Materials
21.28
article

Recyclable Ionogel with Shape Memory‐Assisted Healing Microstructure for Highly Sensitive Ionotronic Pressure Sensor

Lianghao Jia, Yong Zhang, Zhengen Wei, Tao Xiang, Shaobing Zhou
article en
1 citations

Abstract

Surface microstructures have been widely employed in pressure sensors to enhance sensitivity. However, the microstructures are susceptible to irreversible collapse under prolonged cyclic loading, leading to device failure. This work develops a recyclable ionogel (PUF/IL) with shape memory-assisted healing microstructure for highly sensitive ionotronic pressure sensor. Hydrogen bond units (UPy) and fluorinated chain extenders (OHD) are used to regulate the various properties of PUF/IL. Benefiting from the ion-dipole interactions between OHD and ionic liquids (IL), IL can be firmly stabilized in the ionogel network. PUF/IL exhibits exceptional shape-memory properties, demonstrating fixation and recovery rates of 99% and 86%, respectively. More importantly, when the microstructure is mechanically damaged during long-term use, it can be fully recovered through a shape-memory process. Due to the dynamic interactions, PUF/IL shows remarkable recyclability. The mechanical properties, shape memory performance, and pressure-sensing capabilities of recycled PUF/IL retain over 95% of their initial values. Overall, the strategy of healing collapsed microstructures via the shape-memory effect of PUF/IL, combined with its recyclability, effectively improves the long-term reliability and sustainability of pressure sensors. This work provides a solid foundation and creative design ideas for the development of next-generation durable, sustainable, highly sensitive pressure sensors.

SmallVol. 22(13)
Southwest Jiaotong University (CN)
National Natural Science Foundation of China, Southwest Jiaotong University, Fundamental Research Funds for the Central Universities
Responsible consumption and production
Openalex Percentile: Top 3%
Advanced Sensor and Energy Harvesting Materials
21.28
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.