Self‐Healing and Flexible Porous Nickel/Polyurethane Composite Based on Multihealing Systems and Applications
With the development of science and technology, the need for high performance sensors is more and more urgent to deal with different needs and environments. In this study, a flexible strain sensor with performance of self‐healing is developed based on porous nickel as conductive filler and polyureth...
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Veröffentlicht in: | Macromolecular chemistry and physics 2021-12, Vol.222 (23), p.n/a |
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Sprache: | eng |
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Zusammenfassung: | With the development of science and technology, the need for high performance sensors is more and more urgent to deal with different needs and environments. In this study, a flexible strain sensor with performance of self‐healing is developed based on porous nickel as conductive filler and polyurethane (PU) with hydrogen bonding, disulfide bond, and metal coordination bond as polymer matrix. Porous nickel is prepared by a new biotemplates method, and the effects of reaction temperature and concentration of NiCl2·6H2O on the morphology of porous nickel are studied. Polyurethanes containing hydrogen bonding, disulfide bonds, and metal coordination bonds are prepared, and the mechanical properties and self‐healing properties of polyurethanes with different contents of hard and soft segments are studied. A strain sensor is prepared by mixing porous nickel and polyurethane. The effect of filler content on mechanical properties, self‐healing properties, and electrical self‐healing properties is studied. The sensor is attached to the joints of human limbs, and the peak diagram of time‐relative resistance changes is obtained through the cyclic and repeated movements of the limbs. The sensor has excellent sensitivity.
A flexible strain sensor is prepared based on porous nickel as conductive filler and self‐healing polyurethane with hydrogen bonding, disulfide bond, and metal coordination bond as polymer matrix. It has adjustable mechanical properties and self‐healing properties, and can monitor human activity intuitively and accurately by converting human activity into electrical signals. |
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ISSN: | 1022-1352 1521-3935 |
DOI: | 10.1002/macp.202100299 |