2019
DOI: 10.1038/s41598-019-41989-2
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Aggregate-driven reconfigurations of carbon nanotubes in thin networks under strain: in-situ characterization

Abstract: This work focuses on the in-situ characterization of multi-walled carbon nanotube (CNT) motions in thin random networks under strain. Many fine-grain models have been devised to account for CNT motions in carbon nanotube networks (CNN). However, the validation of these models relies on mesoscopic or macroscopic data with very little experimental validation of the physical mechanisms actually arising at the CNT scale. In the present paper, we use in-situ scanning el… Show more

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Cited by 4 publications
(2 citation statements)
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“…Testing samples under various environmental conditions can be achieved by addition of, e.g., a heat chamber, water bath, or placing the CMTT in a glove box under inert atmosphere. Finally, the scalable design and the algorithms can hopefully assist other researchers in exploring, customizing and developing specialized equipment as found for in-situ SEM 19 and TEM 20 characterization.…”
Section: Resultsmentioning
confidence: 99%
“…Testing samples under various environmental conditions can be achieved by addition of, e.g., a heat chamber, water bath, or placing the CMTT in a glove box under inert atmosphere. Finally, the scalable design and the algorithms can hopefully assist other researchers in exploring, customizing and developing specialized equipment as found for in-situ SEM 19 and TEM 20 characterization.…”
Section: Resultsmentioning
confidence: 99%
“…The in-situ characterization of multi-walled carbon nanotube under external strain has uncovered the prominent mechanisms of CNTs motions [ 62 ]. Inkjet printing techniques have provided outstanding results for flexible resistance sensors in terms of their resistance reproducibility [ 68 ]. The carbon nanotube networks (CNNs) fabricated by inkjet-printing present potential applications for flexible resistance strain sensors [ 69 ].…”
Section: Cnts-based Strain Sensorsmentioning
confidence: 99%