Probing the Pore Wall Structure of Nanoporous Carbons Using Adsorption

Nguyen, Thanh X.; Bhatia, Suresh K.

doi:10.1021/la036244p

Cited by 57 publications

(105 citation statements)

References 15 publications

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“…However, the use of such short simulation runs is only feasible when a reasonable guess for initial configuration of the system is known. In the case of activated carbon fibre for instance, Nguyen et al successfully use a graphitic slit-like pore configuration based on the pore size distribution (PSD) and pore wall thickness distribution obtained from interpretation of argon adsorption data [25,38]. On the other hand the use of a highly disordered initial configuration was much less successful for this carbon.…”

Section: Importance Of Multi-stage and Multi-constraint Simulationsmentioning

confidence: 99%

“…To provide further insight, we employed the Finite Wall Thickness Density Functional Theory (FWT-DFT) developed in this laboratory [38,44] to determine the PSD of the HRMC constructed models based on interpretation of simulated argon adsorption isotherm. The results are then compared with the DFT-based PSD obtained from interpretation of experimental argon isotherm.…”

Section: Structural Characterization Of the Hrmc Constructed Modelsmentioning

confidence: 99%

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Hybrid Reverse Monte Carlo simulation of amorphous carbon: Distinguishing between competing structures obtained using different modeling protocols

Farmahini

Bhatia

2015

Carbon

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Please cite this article as: Farmahini, A.H., Bhatia, S.K., Hybrid reverse monte carlo simulation of amorphous carbon: Distinguishing between competing structures obtained using different modelling protocols, Carbon (2014), doi: http://dx.doi.org/10.1016/j.carbon. 2014.11.013 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. ABSTRACTWe explore different multi-stage and multi-constraint modelling strategies using the Hybrid Reverse Monte Carlo (HRMC) technique to develop realistic models for the amorphous structure of silicon carbide derived-carbon, and investigate the effect of modelling parameters on the development of nano-structural features of the constructed models. It is shown that application of long simulations with slow thermal quench rate is essential for modelling of amorphous structures. Nevertheless, very slow quenching rates are shown to lead to the formation of configurations with large fraction of sp 2 carbon, lacking the level of disorder required to match structure-related experimental data. The predicted gas adsorption isotherms are very sensitive to the pore size distribution (PSD), thus the final structure must reasonably reproduce the total pore volume and pore size distribution of the experimental sample. The frequently-observed strong first peak of the DFT-based PSD obtained from argon adsorption is shown to be an artifact of argon inaccessibility. Pore accessibility analysis of the constructed models, as well as MD simulations of gas transport demonstrate that the HRMC constructed structures contain short-range structural anisotropy, however the models are successful in capturing the long range internal energy barriers of amorphous carbon for methane.

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Section: Importance Of Multi-stage and Multi-constraint Simulationsmentioning

confidence: 99%

Section: Structural Characterization Of the Hrmc Constructed Modelsmentioning

confidence: 99%

Hybrid Reverse Monte Carlo simulation of amorphous carbon: Distinguishing between competing structures obtained using different modeling protocols

Farmahini

Bhatia

2015

Carbon

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“…However, a detailed comparison of DFT results with experimental data is not straightforward. Structural and energetic heterogeneity of pores strongly influences on the adsorption in real materials [23,24]. The ways of measurements are different and, therefore, some experimental results contradict to each other [25].…”

Section: Methods Of Calculationsmentioning

confidence: 99%

Classical density functional approach to adsorption of hydrogen in carbon materials

Зубков¹,

Samsonov²,

Grinev³

et al. 2015

Nanosist.: fiz. him. mat.

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The adsorption of hydrogen in carbon adsorbents was investigated at low and high temperatures (20.33, 77, 200 and 300 K) over a wide range of pressures using the classical density functional theory. The adsorbent was simulated by a slit-like pore presented by the gap between two monocarbon (graphene) walls. In most cases, our results demonstrate a good agreement with the available experimental and theoretical results of other authors. A conclusion was made that, contrary to the low temperature region (T < 100 K), at high temperatures (200 and 300 K), predicted values for the adsorption and of the gravimetric density of hydrogen are not sufficient for the practical design of a hydrogen accumulator.

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“…The basic concept relies on the general dependence of the filling pressure and the pore width to the gas amount adsorbed. Since microscopic models can reproduce such a behavior adequately, the Density Functional Theory (Ravikovitch et al, 2006 ;Nguyen & Bhatia, 2004 ;Jagiello & Thommes, 2004) and the Monte Carlo simulation (Do & Do, 2005 ;Nguyen et al, 2005 ;Shao et al, 2004 ;Samios et al, 1997 ;Samios et al, 2000 ;Konstantakou et al, 2007a, Konstantakou et al, 2007b are the most accepted methodologies. A review on both methods is given by (Do & Do, 2003).…”

Section: Application Of the Simulated Adsorption Isotherms To The Chamentioning

confidence: 99%

“…However, the equation fails to apply in micropores, mainly because, a "real" adsorbate phase of molecular dimensions cannot be defined. Molecular models, as for instance the Density Functional Theory (DFT) (Seaton et al, 1989;Lastoskie et al, 1993;Aukett et al, 1992;Ravikovitch et al, 1995;Sosin & Quinn 1995;Scaife et al, 2000;Jagiello & Thommes 2004;Nguyen & Bhatia 2004) and the Monte Carlo (MC) technique (Nilson et al, 2003;Do & Do 2005;Nguyen et al, 2005), can offer a more comprehensive representation of the pore filling process. DFT is computationally less demanding and can provide an accurate description when dealing with simple fluids (spherical molecules) and simple geometries.…”

Section: Introductionmentioning

confidence: 99%