Catalyst deactivation in CVD synthesis of carbon nanotubes

Kuwana, Kazunori; Endo, Hiroyasu; Saito, Kozo; Qian, Dali; Andrews, Rodney; Grulke, Eric A.

doi:10.1016/j.carbon.2004.09.008

Cited by 91 publications

(49 citation statements)

References 12 publications

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“…The model allows determination of gas phase fields for temperature, velocity and species concentration, as well as surface coverage, the CNT growth rate and deposition rate of amorphous carbon. The rate of deposition of carbon along the reactor length is shown in Figure 10 A. Kuwana et al [49] applied a computational fluid dynamics (CFD) model with multi-step chemical reactions to predict the yield of MWCNTs produced from a xylene-based CVD reactor. They developed a laboratoryscale two-step CVD reactor that can synthesize MWCNTs and measured a total yield of nanotubes with a microbalance.…”

Section: Other Modeling Methodsmentioning

confidence: 99%

“…This model predicted uniform velocity and temperature distributions in the furnace region and also the total production rates of CNTs, as shown in Figure 10D, E. Alekseev [53] proposed Figure 10 Influence of temperature, concentration and reactor length on deposition rate, diameter, total production rate and maximum temperature (CFD model and thermodynamic model). (A) Grujicic et al [48] , (B) Kuwana et al [49] , (C) Kuwana and Saito [50] , (D, E) Endo et al [52] , (F) Kaatz et al [55] . Reproduced with permission from Elsevier (A, B, C, D, E) and the American Institute of Physics (F).…”

Section: Other Modeling Methodsmentioning

confidence: 99%

“…The methodology can be readily applied to other CVD systems, so long as the nanotube growth is controlled by the tip growth mechanism. Methodologies have been developed and utilized in a series of papers to study the catalyst deactivation (Kuwana et al [49] ), catalyst nanoparticle formation [50] and the effect of fluid dynamics [51] based on the global reaction mechanism, based on a simple model to predict surface conditions. The model proposed by Endo et al [52] is a simple and useful CFD model based on the global reaction mechanism to predict the production rate of nanotubes in a CVD reactor.…”

Section: Other Modeling Methodsmentioning

confidence: 99%

“…Maruyama and Shibuta [18] experimentally determined carbon deposition rates and CNT growth rates at different processing conditions to validate their model, as shown in Figure 10A. Kuwana et al [49] have compared the total predicted yield of nanotubes over six different time periods, with experimental results as shown in Figure 11 A. Celnik et al [6] used their inception model to investigate the variation of CNT diameter with rate constants and compared the results with experimental findings as shown in Figure 11B. The comparison indicates a good prediction of the nanotube dia meter.…”

Section: Validation Of Modelsmentioning

confidence: 98%

“…The major benchmarking parameters used are yield, production rate and length of carbon nanotubes. (A) Kuwana et al [49] , (B) Celnik et al [6] , (C) Raji et al [16] . Reproduced with permission from Elsevier.…”

Section: Figure 11mentioning

confidence: 99%

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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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Section: Other Modeling Methodsmentioning

confidence: 99%

Section: Other Modeling Methodsmentioning

confidence: 99%

Section: Other Modeling Methodsmentioning

confidence: 99%

Section: Validation Of Modelsmentioning

confidence: 98%

Section: Figure 11mentioning

confidence: 99%

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

Raji

Sobhan

2013

Nanotechnology Reviews

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Carbon Nanotubes, Multi‐Walled

Andrews

Weisenberger

Qian

et al. 2005

Encyclopedia of Inorganic Chemistry

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Well‐aligned carbon multiwalled nanotubes (MWNTs) have been synthesized continuously by pyrolysis of xylene–ferrocene mixtures. To study the MWNT growth mechanism, two‐step processes and various chemical vapor deposition (CVD) parameters have been employed. Transmission electron microscopy observations support a tip‐root growth model of MWNTs by floating catalytic CVD. Hydrocarbon analyzer is used to measure the total carbon balance within the CVD reactor, while mass spectra analyses monitor the concentrations of hydrocarbon species, which helps to understand the catalyst deactivation and pyrolysis chemistry of xylene over catalyst Fe(C) nanoparticles. MWNTs can be treated to attach required functional groups on nanotube walls and/or caps for specific applications by various methods including acid oxidation, reduction, addition of radicals, and cycloadditions. Carbon nanotubes (CNTs) have shown promising applications in advanced CNT–polymer composites. To realize CNT potentials to enhance the properties of matrices, several important issues such as dispersion, orientation, interfacial effects, and processing parameters have been addressed. The dependence of the CNT–polymer composite properties on CNT diameter, length, and interfacial effects has been used to develop models to predict and optimize variables for maximum composite performance. CNT–polymer composites have been developed for enhanced mechanical, electrical, and thermal properties, which have wide applications for the next generation of truly multifunctional materials as well as lighter weights and increased manufacturability over current materials.

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