Printable Carbon Nanotube-Liquid Elastomer-Based Multifunctional Adhesive Sensors for Monitoring Physiological Parameters
| Autor: | Muthamil Selvan T, Simran Sharma, Susmita Naskar, Soumyadeep Mondal, Manish Kaushal, Titash Mondal |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | ACS Applied Materials & Interfaces. 14:45921-45933 |
| ISSN: | 1944-8252 1944-8244 |
| DOI: | 10.1021/acsami.2c13927 |
| Popis: | Developing a printed elastomeric wearable sensor with good conformity and proper adhesion to skin, coupled with the capability of monitoring various physiological parameters, is very crucial for the development of point-of-care sensing devices with high precision and sensitivity. While there have been previous reports on the fabrication of elastomeric multifunctional sensors, research on the printable elastomeric multifunctional adhesive sensor is not very well explored. Herein, we report the development of a stencil printable multifunctional adhesive sensor fabricated in a solvent-free condition, which demonstrated the capability of having good contact with skin and its ability to function as a temperature and strain sensor. Functionalized liquid isoprene rubber was selected as the matrix while carboxylated multiwalled carbon nanotubes (c-CNTs) were used as the nanofiller. The selection of the above model compounds facilitated the printability and also helped the same composition to demonstrate stretchability and adhesiveness. A realistic three-dimensional microstructure (representative volume element model) was generated through a computational framework for the current c-CNT-liquid elastomer. Further computational simulations were performed to test and validate the correlation between electrical responses to that of experimental studies. Various physiological parameters like motion sensing, pulse, respiratory rate, and phonetics detection were detected by leveraging the electrically resistive nature of the sensor. This development route can be extended toward developing different innovative adhesives for point-of-care sensing applications. |
| Databáze: | OpenAIRE |
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