A Magnetically Self‐Aligning, Fast Full‐Device Self‐Healing, Skin‐Attachable Liquid Metal Strain Sensor Based on Photothermal Polyurethane

Abstract There is a growing need for research on self‐healing materials capable of spontaneously repairing physical damage, allowing the fabrication of highly durable wearable devices featuring flexibility and stretchability. Herein, the study reports on the fabrication of a novel, magnetically aligning, fully and rapidly self‐healing skin‐attachable biosensor based on newly synthesized photothermally self‐healing polyurethane. By introducing photothermal amine‐capped aniline trimers to selectively self‐healable polyurethane, the synthesized self‐healing polymer achieves a fast and high recovery rate of 81.1% from complete bisection upon laser irradiation for just 3 min. Additionally, a thin‐film type strain sensor fabricated via the spray patterning of liquid metal EGaIn as an electrode onto the surface of the self‐healing polymer exhibits a high sensitivity to strain from deformation, enabling the real‐time monitoring of bio‐signals. Furthermore, the integration of a magnetic aligning layer directly patterned and embedded onto the self‐healing polymer enhances the self‐healing performance of the sensor after damage by 4.3 times on average, compared to when using manual alignment. In short, this work demonstrates a high‐performance fully self‐healing electronic device via the synthesis of novel fast self‐healing photothermal polymers and the introduction of patterned liquid metal electrodes and magnetic alignment layers.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2024-12-11
DOI
https://doi.org/10.1002/adfm.202411786
Citations
13
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
2.40

Funders

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

A Magnetically Self‐Aligning, Fast Full‐Device Self‐Healing, Skin‐Attachable Liquid Metal Strain Sensor Based on Photothermal Polyurethane

Yongju Kim, Jeong Sook Ha, Somin Kim, Jung Wook Kim
13 citations
Advanced Functional Materials
Advanced Sensor and Energy Harvesting Materials
2.40
article

A Magnetically Self‐Aligning, Fast Full‐Device Self‐Healing, Skin‐Attachable Liquid Metal Strain Sensor Based on Photothermal Polyurethane

Yongju Kim, Jeong Sook Ha, Somin Kim, Jung Wook Kim
article en
13 citations

Abstract

Abstract There is a growing need for research on self‐healing materials capable of spontaneously repairing physical damage, allowing the fabrication of highly durable wearable devices featuring flexibility and stretchability. Herein, the study reports on the fabrication of a novel, magnetically aligning, fully and rapidly self‐healing skin‐attachable biosensor based on newly synthesized photothermally self‐healing polyurethane. By introducing photothermal amine‐capped aniline trimers to selectively self‐healable polyurethane, the synthesized self‐healing polymer achieves a fast and high recovery rate of 81.1% from complete bisection upon laser irradiation for just 3 min. Additionally, a thin‐film type strain sensor fabricated via the spray patterning of liquid metal EGaIn as an electrode onto the surface of the self‐healing polymer exhibits a high sensitivity to strain from deformation, enabling the real‐time monitoring of bio‐signals. Furthermore, the integration of a magnetic aligning layer directly patterned and embedded onto the self‐healing polymer enhances the self‐healing performance of the sensor after damage by 4.3 times on average, compared to when using manual alignment. In short, this work demonstrates a high‐performance fully self‐healing electronic device via the synthesis of novel fast self‐healing photothermal polymers and the introduction of patterned liquid metal electrodes and magnetic alignment layers.

Advanced Functional MaterialsVol. 35(3)
Korea University (KR)
Ministry of Science and ICT, South Korea
Openalex Percentile: Top 11%
Advanced Sensor and Energy Harvesting Materials
2.40
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.