Alignment Control of Carbon Nanotube Forest from Random to Nearly Perfectly Aligned by Utilizing the Crowding Effect

Alignment represents an important structural parameter of carbon nanotubes (CNTs) owing to their exceptionally high aspect ratio, one-dimensional property. In this paper, we demonstrate a general approach to control the alignment of few-walled CNT forests from nearly random to nearly ideally aligned...

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Veröffentlicht in:ACS nano 2012-07, Vol.6 (7), p.5837-5844
Hauptverfasser: Xu, Ming, Futaba, Don N, Yumura, Motoo, Hata, Kenji
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Futaba, Don N
Yumura, Motoo
Hata, Kenji
description Alignment represents an important structural parameter of carbon nanotubes (CNTs) owing to their exceptionally high aspect ratio, one-dimensional property. In this paper, we demonstrate a general approach to control the alignment of few-walled CNT forests from nearly random to nearly ideally aligned by tailoring the density of active catalysts at the catalyst formation stage, which can be experimentally achieved by controlling the CNT forest mass density. Experimentally, we found that the catalyst density and the degree of alignment were inseparably linked because of a crowding effect from neighboring CNTs, that is, the increasing confinement of CNTs with increased density. Therefore, the CNT density governed the degree of alignment, which increased monotonically with the density. This relationship, in turn, allowed the precise control of the alignment through control of the mass density. To understand this behavior further, we developed a simple, first-order model based on the flexural modulus of the CNTs that could quantitatively describe the relationship between the degree of alignment (HOF) and carbon nanotube spacing (crowding effect) of any type of CNTs.
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source American Chemical Society Journals
subjects Alignment
Carbon nanotubes
Catalysis
Catalysts
Crowding
Density
Forests
Mathematical models
Modulus of rupture in bending
title Alignment Control of Carbon Nanotube Forest from Random to Nearly Perfectly Aligned by Utilizing the Crowding Effect
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