Alen Oseli (Author), Alenka Vesel (Author), Ema Žagar (Author), Lidija Slemenik Perše (Author)

Abstract

The reinforcing and conductive performance of carbon nanotube polymer-based nanocomposites depends on the established network and its configuration. Within this study, we report on the underlying mechanisms of such network formation utilizing single-walled carbon nanotubes (SWCNTs) in low- and high-density polyethylene matrices. Mechanisms were theoretically evaluated through Doi-Edwards theory and experimentally confirmed through plasma etching coupled with electron microscopy as well as rheological flow tests. Results showed that the established network is constructed from SWCNT bundles, which geometrically entangle at a critical volume fraction [phi]v,crit (number of rods: [beta approximately equal to] 30). Below [phi]v,crit, the bundles behave as individual units and may align in the flow direction. Above [phi]v,crit, the rotation of bundles is constrained by neighboring units, leading to a random network configuration. Moreover, the theory successfully explains SWCNT bundle behavior as a Brownian entity and predicts network formation through diminishing thermo- and hydro-dynamically driven diffusion, which can be manipulated during the production to enhance reinforcing/conductive functionality of such materials.

Keywords

nanocomposites;single-walled carbon nanotubes;network formation;molecular dynamics;Doi-Edwards theory;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FS - Faculty of Mechanical Engineering
UDC: 620.168(045)
COBISS: 58206467 Link will open in a new window
ISSN: 0024-9297
Views: 265
Downloads: 46
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Other data

Secondary language: Slovenian
Secondary keywords: nanokompoziti;eno-stenske ogljikove nano-cevke;nastanek omrežja;molekularna dinamika;Doi-Edwards teorija;
Type (COBISS): Article
Embargo end date (OpenAIRE): 2022-04-13
Pages: str. 3334-3346
Volume: ǂVol. ǂ54
Issue: ǂiss. ǂ7
Chronology: Apr. 2021
DOI: 10.1021/acs.macromol.0c02763
ID: 12855959