Understanding the Nucleation Mechanisms of Carbon Nanotubes in Catalytic Chemical Vapor Deposition

Amara, Hakim; Bichara, Christophe; Ducastelle, F.

doi:10.1103/physrevlett.100.056105

Cited by 150 publications

(182 citation statements)

References 27 publications

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“…This was used to study these systems at 1000 or 1500 K and provides good statistics for a variety of SWNT chiralities and initial distributions of the Ni atoms. This TB Hamiltonian has been developed specifically for nickel-carbon systems [13], and has been successfully used by Amara et al [12] to study the formation of graphitic carbon structures on Ni surfaces and clusters. Their study showed that solubility of carbon atoms in nickel is limited, but that carbon atoms are also stable at subsurface sites.…”

Section: Methodsmentioning

confidence: 99%

“…Previous calculations include density functional theory (DFT) geometry optimisation [5,6], molecular dynamics [7,8], direct dynamics based on tight binding [9] and DFT [10,11] forces, and tight binding Monte Carlo (TBMC) simulations [12][13][14]. For example, previous TBMC simulations at 1000 K showed that Ni atoms that are uniformly distributed over an SWNT wall aggregate and diffuse to the open end of the SWNT, where they remain for the remainder of the simulation [14].…”

Section: Introductionmentioning

confidence: 99%

“…Our TBMC simulations are limited to carbon systems attached to a single metal, i.e., Ni, since the semiempirical parameters have not been fitted for other metals [13]. However, many experimental growth methods use metal alloys such as the Co:Mo [3] alloy mentioned above.…”

Section: Introductionmentioning

confidence: 99%

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Density functional theory and tight binding-based dynamical studies of carbon metal systems of relevance to carbon nanotube growth

et al. 2009

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Density functional theory (DFT) and tight binding (TB) models have been used to study systems containing single-walled carbon nanotubes (SWNTs) and metal clusters that are of relevance to SWNT growth and regrowth. In particular, TB-based Monte Carlo (TBMC) simulations at 1000 or 1500 K show that Ni atoms that are initially on the surface of the SWNT or that are clustered near the SWNT end diffuse to the nanotube end so that virtually none of the Ni atoms are located inside the nanotube. This occurs, in part, due to the lowering of the Ni atom energies when they retract from the SWNT to the interior of the cluster. Aggregation of the atoms at the SWNT end does not change the chirality within the simulation time, which supports the application of SWNT regrowth (seeded growth) as a potential route for chirality-controlled SWNT production. DFT-based geometry optimisation and direct dynamics at 2000 K show that Cr and Mo atoms in Cr 5 Co 50 and Mo 5 Co 50 clusters prefer to be distributed in the interior of the clusters. Extension of these calculations should deepen our understanding of the role of the various alloy components in SWNT growth.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Density functional theory and tight binding-based dynamical studies of carbon metal systems of relevance to carbon nanotube growth

et al. 2009

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“…The incorporation of C 2 fragments to a pre-formed cap with defined chirality was investigated by Gómez-Gualdrón et al [117]. Using a grand canonical MC simulation, Amara et al [118] investigated the nucleation of carbon caps on small nickel nanoparticles. A tip growth mechanism was demonstrated by Charlier et al [119].…”

Section: Detailed Atomistic Simulations Of Nanostructure Growth Procementioning

confidence: 99%

Computer modelling of the plasma chemistry and plasma-based growth mechanisms for nanostructured materials

Bogaerts¹,

Eckert²,

Mao³

et al. 2011

J. Phys. D: Appl. Phys.

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In this review paper, an overview is given of different modeling efforts for plasmas used for the formation and growth of nanostructured materials. This includes both the plasma chemistry, providing information on the precursors for nanostructure formation, as well as the growth processes itself. We limit ourselves to carbon (and silicon) nanostructures. Examples of the plasma modeling comprise nanoparticle formation in silane and hydrocarbon plasmas, as well as the plasma chemistry giving rise to carbon nanostructure formation, such as (ultra)nanocrystalline diamond ((U)NCD) and carbon nanotubes (CNTs). The second part of the paper deals with the simulation of the (plasma-based) growth mechanisms of the same carbon nanostructures, i.e., (U)NCD and CNTs, both by mechanistic modeling and detailed atomistic simulations. IntroductionLow temperature plasmas are playing an increasingly important role for the formation and growth of nanostructures and nanostructured materials (e.g., [1][2][3][4][5][6][7]). To improve the performance of these plasma growth processes, a good insight is desired in the plasma and in the interaction with the growing nanostructures. This insight can be obtained by experimental research, but the latter is not always straightforward, in view of the small dimensions of the nanomaterials and the possible disturbance of the plasma characteristics, e.g., when introducing a probe. Therefore, computer simulations can be very useful to assist in the experimental developments.In the present paper, we will give an overview of different modeling efforts that have been presented in the literature for plasmas used for nanostructure formation. This includes two different aspects. First, a thorough understanding of the plasma behavior is needed. This comprises background gas flow and heating (i.e., fluid dynamics), gas breakdown, transport and heating of the electrons and the so-called heavy particles, as well as the plasma chemistry, i.e., creation and destruction of the various plasma species by chemical reactions. Modeling of the plasma chemistry can give indications on which species are important precursors for the growth of nanostructured materials and how the plasma operating conditions can be tuned to optimize the growth process. Therefore, in this paper we will mainly focus on the plasma chemistry modeling. Several plasma modeling approaches exist in literature, such as analytical models, zero-dimensional (0D) chemical kinetics simulations, fluid models (describing the chemical kinetics as well as fluid dynamics), solving the Boltzmann transport equation, Monte Carlo (MC) and particle-in-cell (PIC)-MC simulations, as well as hybrid methods, combining the above (e.g., MC + fluid) models. For describing the plasma chemistry, the 0D chemical kinetics approach is often applied, as it can take into account a large number of different species and reactions without too much computational effort. However, it assumes a spatially uniform plasma composition and does not consider transport of the plasm...

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“…The simulations revealed that the inner walls of the bamboo structure start to nucleate at the junction between the outer nanotube wall and the catalyst particle. Amara et al [29] studied the nucleation of carbon caps on small nickel clusters using a tight-binding model coupled to grand canonical Monte Carlo simulations and found that an optimal chemical potential window exists for the carbon atom, to nucleate nanotube caps whose curvature matches with the local curvature of the catalyst particles. The solubility of carbon atoms in the outermost Ni layers depends on the initial state of the catalyst (crystalline or disordered) and on the thermodynamic conditions.…”

Section: Discrete Computational Modelingmentioning

confidence: 99%

Simulation and modeling of carbon nanotube synthesis: current trends and investigations

Raji

Sobhan

2013

Nanotechnology Reviews

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A review of significant investigations reported on simulating the nucleation and growth processes of carbon nanotubes (CNTs) using different modeling techniques is presented here. Special emphasis is given to the chemical vapor deposition method, being the cheapest and most versatile of the fabrication methods. The modeling methods involve the conventional computational fluid dynamics approaches as well as discrete computation techniques. Some in-house investigations utilizing chemical kinetic modeling and discrete computations to predict the growth of CNTs using the chemical vapor deposition method are also discussed. The modeling and simulation techniques reviewed here are expected to assist in the design of chirality-specific single-walled CNT synthesis systems.

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Understanding the Nucleation Mechanisms of Carbon Nanotubes in Catalytic Chemical Vapor Deposition

Cited by 150 publications

References 27 publications

Density functional theory and tight binding-based dynamical studies of carbon metal systems of relevance to carbon nanotube growth

Density functional theory and tight binding-based dynamical studies of carbon metal systems of relevance to carbon nanotube growth

Computer modelling of the plasma chemistry and plasma-based growth mechanisms for nanostructured materials

Simulation and modeling of carbon nanotube synthesis: current trends and investigations

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