2018
DOI: 10.1016/j.compscitech.2018.05.017
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Stretchable and compressible strain sensor based on carbon nanotube foam/polymer nanocomposites with three-dimensional networks

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Cited by 68 publications
(45 citation statements)
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“…According to the work of Zha et al., 16 the presence of CB at weight fraction higher than 3% inside the composite emphasizes the reorientation of MWCNT and thus the sliding phenomenon. The resulting losses of conductive paths inside the matrix are revealed by the variations of the electrical impedance This result is similar to those obtained by Hao et al., 14 Ku-Herrera and Aviles, 11 Mitrakos, 15 Spinelli et al. 3 and Wang et al.…”
Section: Resultssupporting
confidence: 87%
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“…According to the work of Zha et al., 16 the presence of CB at weight fraction higher than 3% inside the composite emphasizes the reorientation of MWCNT and thus the sliding phenomenon. The resulting losses of conductive paths inside the matrix are revealed by the variations of the electrical impedance This result is similar to those obtained by Hao et al., 14 Ku-Herrera and Aviles, 11 Mitrakos, 15 Spinelli et al. 3 and Wang et al.…”
Section: Resultssupporting
confidence: 87%
“…Thus, the CNTs orientate in the transverse direction of the mechanical loading, leading to fewer contacts in the conductive network and higher electrical resistance. Similar results were obtained in the studies by Hao et al., 14 Mitrakos 15 and Spinelli et al. 3…”
Section: Introductionsupporting
confidence: 90%
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“…Carbon nanotubes represent the foundation for most of the conventional stretchable strain sensors 1,[8][9][10][11][12][13] , owing to performance characteristics which considerably exceed from known metal/metal oxides or organic semiconductors based sensors [14][15][16] , including large stretchability, high piezoresistivity and long term stability under mechanical strain. More precisely, single-walled carbon nanotubes (SWCNTs) possess one dimensional morphology with high aspect ratio to offer high internal piezoresistivity for use in strain sensors 17,18 .…”
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confidence: 99%