Reverse Monte Carlo analysis of the structure of glassy carbon using electron-microscopy data

O’Malley, Brendan; Snook, Ian K.; McCulloch, D. G.

doi:10.1103/physrevb.57.14148

Cited by 64 publications

(49 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In principle, any experimental or physically motivated function which may be calculated from the positions of an assembly of atoms may be used within the RMC procedure to produce model atomic structures consistent with experimental observations. Recent work by O'Malley et al [63] has shown that the inclusion of a constraint, which biases the RMC algorithm to produce desired proportions of experimentally determined atomic coordination fractions, improves the microstructural description of glassy carbon materials.…”

Section: Reverse Monte Carlo Modellingmentioning

confidence: 98%

“…Extending on the work of O'Malley et al [63], we have recently incorporated the environment dependent interaction potential (EDIP), which was developed by Marks [64] for carbon, into the algorithm; thereby combining Metropolis Monte Carlo methods with those of RMC. As described in our previous publications [56,57], the current hybrid algorithm, which will be referred to here as 'HRMC', allows the EDIP energy of structures to be minimised whilst also maintaining statistical agreement with experimental observations, thereby improving the physical nature of the atomic configurations produced for carbonaceous materials.…”

Section: Reverse Monte Carlo Modellingmentioning

confidence: 99%

“…In order to provide some estimate of the nature of the char X microstructure in comparison to that of other carbonaceous materials, some high resolution TEM images were acquired from char X in addition to a previously investigated [57,63] V25 glassy carbon sample.…”

Section: Electron Diffractionmentioning

confidence: 99%

See 2 more Smart Citations

Microstructure of an industrial char by diffraction techniques and Reverse Monte Carlo modelling

Petersen

Yarovsky

Snook

et al. 2004

Carbon

View full text Add to dashboard Cite

Section: Reverse Monte Carlo Modellingmentioning

confidence: 98%

Section: Reverse Monte Carlo Modellingmentioning

confidence: 99%

See 1 more Smart Citation

Microstructure of an industrial char by diffraction techniques and Reverse Monte Carlo modelling

Petersen

Yarovsky

Snook

et al. 2004

Carbon

View full text Add to dashboard Cite

“…Their modified version of the RMC algorithm constrains the formation of unphysical 3-membered carbon rings, as well as carbon atoms that are bonded to more than four atoms in their vicinity. Shortly after, O'Malley and co-workers [11] introduced a CRMC algorithm for modeling of the structure of glassy carbon by controlling the atomic coordination number of the system following…”

Section: ୀଵmentioning

confidence: 99%

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

Farmahini

Bhatia

2015

Carbon

View full text Add to dashboard Cite

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.

show abstract

“…However, it possibly suggests the amount of non- Assuming the widths of these two peaks reflect, in part, distortion of the graphenic structure, Table 4 shows that this angle takes on a range of values that is invariant with activation and in line with those obtained from Reverse Monte Carlo simulation of nanoporous carbons [80][81][82].…”

Section: Xrd Analysismentioning

confidence: 73%

A multi-method study of the transformation of the carbonaceous skeleton of a polymer-based nanoporous carbon along the activation pathway

Hu¹,

Liu²,

Weyland³

et al. 2015

Carbon

View full text Add to dashboard Cite

Reverse Monte Carlo analysis of the structure of glassy carbon using electron-microscopy data

Cited by 64 publications

References 15 publications

Microstructure of an industrial char by diffraction techniques and Reverse Monte Carlo modelling

Microstructure of an industrial char by diffraction techniques and Reverse Monte Carlo modelling

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

A multi-method study of the transformation of the carbonaceous skeleton of a polymer-based nanoporous carbon along the activation pathway

Contact Info

Product

Resources

About