Water transport through (7,7) carbon nanotubes of different lengths using molecular dynamics

Nicholls, William D.; Borg, Matthew K.; Lockerby, Duncan A.; Reese, Jason M.

doi:10.1007/s10404-011-0869-3

Cited by 105 publications

(72 citation statements)

References 27 publications

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“…1 and is similar to our previous study [9]. Two graphene sheets are positioned at the inlet and outlet of the CNT to form a simplified CNT membrane representation.…”

Section: Simulation Methodologymentioning

confidence: 91%

“…We have shown in a previous study [9] that the flow enhancement factor, defined as the ratio of the MD simulated mass flow rate to the hydrodynamic prediction, increases linearly with CNT length for a fixed pressure difference. If this trend continues up to the lengths used in experiments, which can be 2-5 µm, then the flow enhancement factor would far exceed those reported from experiments.…”

Section: Introductionmentioning

confidence: 85%

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Water transport through carbon nanotubes with defects

Nicholls

Borg

Lockerby

et al. 2012

Molecular Simulation

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This version is available at https://strathprints.strath.ac.uk/41101/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the ABSTRACTNon-equilibrium molecular dynamics simulations are performed to investigate how changing the number of structural defects in the wall of a (7,7) single-wall carbon nanotube (CNT) affects water transport and internal fluid dynamics. Structural defects are modelled as vacancy sites (missing carbon atoms). We find that, while fluid flow rates exceed continuum expectations, increasing numbers of defects lead to significant reductions in fluid velocity and mass flow rate. The inclusion of such defects causes a reduction in the water density inside the nanotubes and disrupts the nearly-frictionless water transport commonly attributed to CNTs.

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“…1 and is similar to our previous study [9]. Two graphene sheets are positioned at the inlet and outlet of the CNT to form a simplified CNT membrane representation.…”

Section: Simulation Methodologymentioning

confidence: 91%

Section: Introductionmentioning

confidence: 85%

Water transport through carbon nanotubes with defects

Nicholls

Borg

Lockerby

et al. 2012

Molecular Simulation

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“…The optical properties of SWCNTs have been simulated in various studies. [6][7][8] Although several experimental [9][10][11][12][13][14][15][16][17][18][19][20][21] and theoretical studies [22][23][24][25][26] have considered (7, 7) the carbon nanotubes properties, the optical spectrum of CNTs (7,7) has not been probed yet.…”

Section: Introductionmentioning

confidence: 99%

Optical properties of armchair (7, 7) single walled carbon nanotubes

Gharbavi

Badehian

2015

AIP Advances

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Full potential linearized augmented plane waves method with the generalized gradient approximation for the exchange-correlation potential was applied to calculate the optical properties of (7, 7) single walled carbon nanotubes. The both x and z directions of the incident photons were applied to estimate optical gaps, dielectric function, electron energy loss spectroscopies, optical conductivity, optical extinction, optical refractive index and optical absorption coefficient. The results predict that dielectric function, ε (ω), is anisotropic since it has higher peaks along z-direction than x-direction. The static optical refractive constant were calculated about 1.4 (z-direction) and 1.1 (x- direction). Moreover, the electron energy loss spectroscopy showed a sharp π electron plasmon peaks at about 6 eV and 5 eV for z and x-directions respectively. The calculated reflection spectra show that directions perpendicular to the tube axis have further optical reflection. Moreover, z-direction indicates higher peaks at absorption spectra in low range energies. Totally, increasing the diameter of armchair carbon nanotubes cause the optical band gap, static optical refractive constant and optical reflectivity to decrease. On the other hand, increasing the diameter cause the optical absorption and the optical conductivity to increase. Moreover, the sharp peaks being illustrated at optical spectrum are related to the 1D structure of CNTs which confirm the accuracy of the calculations.

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“…The CFD mesh is chosen to be fine enough to safely give mesh-independent results for mass flow rate; given that the cost of the CFD simulations is extremely small, achieving this poses no particular problem. The pressure difference between the reservoirs is set to be 200 MPa because it is very challenging to obtain useful information from MD using only low pressure differences due to the extended sampling times required to filter low-velocity signals from the thermal noise (Nicholls et al 2012). These high pressure (and consequently density) differences make the CFD predictions even more challenging.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…5, except that the two reservoirs of water, held at different pressures, are now separated by a (15,15) CNT of length 50 nm and diameter approximately 2 nm; since the domain is periodic in the y-and z-directions, this setup represents a regularly repeated array of CNTs. The flow of water through CNTs has recently been the focus of substantial research effort (Alexiadis and Kassinos 2008) mainly due to the extremely high flow rates that have been both predicted (Nicholls et al 2012) and measured (Mattia and Gogotsi 2008;Whitby and Quirke 2007). These flow rates are often expressed as an enhancement factor, which is the ratio of water flow rates along the CNT to those predicted by classical fluid dynamics (i.e.…”

Section: Water Flow Through Carbon Nanotube (Cnt) Membranesmentioning

confidence: 99%

Molecular dynamics pre-simulations for nanoscale computational fluid dynamics

Holland

Lockerby

Borg

et al. 2014

Microfluid Nanofluid

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We present a procedure for using molecular dynamics (MD) simulations to provide essential fluid and interface properties for subsequent use in computational fluid dynamics (CFD) calculations of nanoscale fluid flows. The MD pre-simulations enable us to obtain an equation of state, constitutive relations, and boundary conditions for any given fluid/solid combination, in a form that can be conveniently implemented within an otherwise conventional Navier-Stokes solver. Our results demonstrate that these enhanced CFD simulations are then capable of providing good flow field results in a range of complex geometries at the nanoscale. Comparison for validation is with full-scale MD simulations here, but the computational cost of the enhanced CFD is negligible in comparison with the MD. Importantly, accurate predictions can be obtained in geometries that are more complex than the planar MD pre-simulation geometry that provides the nanoscale fluid properties. The robustness of the enhanced CFD is tested by application to water flow along a (15,15) carbon nanotube, and it is found that useful flow information can be obtained.

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Water transport through (7,7) carbon nanotubes of different lengths using molecular dynamics

Cited by 105 publications

References 27 publications

Water transport through carbon nanotubes with defects

Water transport through carbon nanotubes with defects

Optical properties of armchair (7, 7) single walled carbon nanotubes

Molecular dynamics pre-simulations for nanoscale computational fluid dynamics

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