journal article·2019-09

Ultrafast Self‐Healing and Injectable Conductive Hydrogel for Strain and Pressure Sensors

Fengming Ye, Meng Li, Dingning Ke, Liping Wang, Yi Lu

Advanced Materials Technologies· Volume 4· Issue 9
Publisher page

Abstract

Abstract The in vivo detection of body motion and subtle physiological signals, including respiration and sphygmus waves, remains a major challenge. High‐precision, miniature sensors are urgently needed to investigate physiological responses against particular stimuli. Injectable conductive self‐healing (ICSH) hydrogels are promising candidates for flexible wearable electronics in healthcare monitoring, owing to their mechanical and electrical characteristics. Given this, an interpenetrating polymer network (IPN) of multiwalled carbon nanotube‐poly(3,4‐ethylenedioxythiophene)/poly(styrenesulfonate)‐polyacrylamide‐poly(vinyl alcohol)/borax composite hydrogel (CNT‐PEDOT‐PAM‐PVA) is cross‐linked in a simplified process to achieve reliable physiological signal detection. The CNT‐PEDOT‐PAM‐PVA IPN offers ultra‐low Young's modulus, high stretchability, rapid self‐healing, and injectability. A miniature strain sensor fabricated via material injection shows consistent and linear responses to mechanical stimuli. It can distinguish between the respiration amplitude and frequency of a mouse during different activities. Pressure micro‐sensors fabricated through bottom‐up printing–injecting can successfully monitor precise sphygmus signals from the human radial and carotid arteries. The feasibility and advantages of ICSH hydrogels in the detection of physiological signals in vivo are demonstrated. Such miniature sensors can contribute to healthcare monitoring and the understanding of the biological basis of a particular behavior or neuropsychiatric disorder.
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Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Muscle activation and electromyography studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

The Brain Cognition and Brain Disease Institute Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen‐Hong Kong Institute of Brain Science‐Shenzhen Fundamental Research Institutions Shenzhen 518055 China

Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen 518055 China

Nano Science and Technology Institute University of Science and Technology of China Suzhou 215123 China

Experiment and Innovation Center Harbin Institute of Technology Shenzhen Graduate School Shenzhen 518055 China

Funding

National Natural Science Foundation of China · CAS-SAFEA International Partnership Program for Creative Research Teams · Science and Technology Planning Project of Guangdong Province

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