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Issue 20, 2017
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Statistical modelling and simulation of nanohybrid shish-kebab architecture of PE-b-PEG copolymers and carbon nanotubes

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Abstract

Carbon nanotubes have been known to develop hierarchically ordered polymer nanocomposites by virtue of epitaxial crystallization. A unique product of CNT induced crystallization is generation of nanohybrid shish-kebab (NHSK) structure, which has gained tremendous attention owing to its unique applications. However, research faces major challenges in terms of producing tunable patterns on CNTs, which are largely governed by precise control of the crystallization parameters. Conventional methods of experimentation can mislead the effect of experimental conditions on NHSK structure. The effect of crystallization time, undercooling temperature and polymer concentration on the NHSK architecture of carbon nanotubes (CNTs) and on a block copolymer, polyethylene-b-polyethylene glycol (PE-b-PEG), was studied in this work by applying the Response Surface Methodology (RSM). The present novel investigation mainly reports the statistical models that can be used to predict the different NHSK structural features such as diameter, periodicity, and thickness by including the interaction and quadratic effects of experimental variables. The developed models are in very good agreement with the experimental data and are statistically significant. Our novel approach can be used to better understand the interplay between various crystallization parameters for periodic patterning on carbon nanotubes to generate tunable hierarchical structures.

Graphical abstract: Statistical modelling and simulation of nanohybrid shish-kebab architecture of PE-b-PEG copolymers and carbon nanotubes

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Publication details

The article was received on 26 Jan 2017, accepted on 20 Apr 2017 and first published on 26 Apr 2017


Article type: Paper
DOI: 10.1039/C7CP00597K
Citation: Phys. Chem. Chem. Phys., 2017,19, 13348-13360
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    Statistical modelling and simulation of nanohybrid shish-kebab architecture of PE-b-PEG copolymers and carbon nanotubes

    T. Le, N. Collazos, A. Simoneaux, S. Murru, D. Depan and R. Subramaniam, Phys. Chem. Chem. Phys., 2017, 19, 13348
    DOI: 10.1039/C7CP00597K

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