A kinetic model of CH4 decomposition and filamentous carbon formation on supported Co catalysts

Zhang, Yi; Smith, Kevin J.

doi:10.1016/j.jcat.2005.02.010

Cited by 48 publications

(38 citation statements)

References 30 publications

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“…The carbon filaments were present in great amounts on the samples CA, MgCA and NiCA, which is in agreement with the higher activity of these samples. It is believed that the formation of filaments preserves the catalyst activity [52]; therefore, when the carbon rate (or catalytic activity) is higher, the carbon nanotubes production is higher. According to the TPO results, these filaments correspond to single-walled carbon nanotubes (SWNT).…”

Section: Characterization Of the Carbonmentioning

confidence: 99%

Catalytic Decomposition of Methane Over M–Co–Al Catalysts (M = Mg, Ni, Zn, Cu)

2011

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The catalytic decomposition of methane over M-Co-Al (M = Mg, Ni, Zn, Cu) was studied. The samples were prepared by co-precipitation and characterized by S BET , TGA, DTA, TPR and XRD. The carbon produced in the reaction was characterized by SEM and TPO. Activity tests were carried out in a thermobalance between 500 and 750°C. The results show that the textural properties of the calcined samples did not change significantly with the partial substitution of Co by Mg, Ni, Zn or Cu. On the other hand, there were marked differences in the reduced samples. There was a strong influence on the reducibility of cobalt oxides in the presence of Ni or Cu. Nickel promoted the reduction of Co 3 O 4 at the same temperature as the NiO phase, whereas copper strongly decreased the reduction temperature of both Co 3 O 4 and CoAl 2 O 4 due to a synergistic effect between Cu and Co. The sample containing Cu resulted in low catalytic activity in the whole temperature range because the reduction conditions promoted the formation of a Cu-Co alloy. In the reaction carried out at 700°C, the observed activity was Co-Al [ Mg-CoAl [ Ni-Co-Al. All the samples were deactivated by encapsulation under these conditions due to high rates of carbon deposition. The carbon produced was mainly carbon nanotubes, except for the Cu-Co-Al sample, which produced mostly amorphous carbon.

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Section: Characterization Of the Carbonmentioning

confidence: 99%

Catalytic Decomposition of Methane Over M–Co–Al Catalysts (M = Mg, Ni, Zn, Cu)

2011

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“…Table 1 summarizes the different mechanistic growth models published in recent years, indicating the processes included in each model, the reactor type (CVD or PE-CVD) and the simulation method. From this overview it is clear that the mechanistic models can be divided into three groups from simulation point of view, i.e., kinetic models [92][93][94][95][96][97][98][99], multiphysics, multiphase integrated models [100][101][102][103] and kinetic Monte Carlo (MC) models [104][105][106][107]. Puretzky and co-workers [92] presented a kinetic model for the CVD-based growth of vertically aligned nanotube arrays (VANTAs) from C 2 H 2 , based on in situ measurements.…”

Section: (B) Cnts and Related Structuresmentioning

confidence: 99%

“…A kinetic model of CH 4 decomposition and filamentous carbon formation on supported Co catalysts was developed by Zhang and Smith [94]. The geometry of the catalyst particles was considered and approximated as a slab with height of 2/3 d p in the model, where d p denotes the average diameter of a catalyst particle.…”

Section: (B) Cnts and Related Structuresmentioning

confidence: 99%

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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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“…3,4 Such functionalized tips can also be used to attract other molecules for various applications, e.g., for functionalization with protonated amines ͑-NH 3 + Cl − ͒ that add positive charges to CNTs, which allows binding to negatively charged RNA molecules. 5 Continuum scale CNT growth models that typically assume a certain growth mode 6 can also benefit from these predictions.…”

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confidence: 99%