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A novel algorithm to model the influence of host lattice flexibility in molecular dynamics simulations: Loading dependence of self-diffusion in carbon nanotubes
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10.1063/1.2185619
/content/aip/journal/jcp/124/15/10.1063/1.2185619
http://aip.metastore.ingenta.com/content/aip/journal/jcp/124/15/10.1063/1.2185619

Figures

Image of FIG. 1.
FIG. 1.

(Color online) Sketch of the carbon nanotube methane system.

Image of FIG. 2.
FIG. 2.

Mean-squared displacement (MSD) for methane inside a (20,0) CNT at . One MSD corresponds to a bulk pressure of (low loading), and the other to a bulk pressure of (high loading). The linear fits were applied between 1 and .

Image of FIG. 3.
FIG. 3.

Schematic sketch of the carbon nanotube flexibility influence on self-diffusion.

Image of FIG. 4.
FIG. 4.

(Color online) Illustration of the Lowe-Andersen radius (collision radius) . One particle (bigger) is nonthermalized; the velocities of the other particle are recalculated with certain probabilities. The component is recalculated with the probability . Whereas, the and components are recalculated with the probability .

Image of FIG. 5.
FIG. 5.

(Color online) Heating curves for heating ideal gases in a (20,0) carbon nanotube, calculated with a flexible CNT (thick lines) or with the LA-IFC thermostat (thin lines). The LA-IFC curves are calculated with the data sets where the collision radius corresponds to the maximum in the RDF (see Table II). is the conventional temperature , and the temperature for the direction only. The temperature switch is defined to take place at a time . All heating curves are averages over 100 independent simulations.

Image of FIG. 6.
FIG. 6.

(Color online) Normalized velocity autocorrelation functions for diffusion inside a (20,0) CNT at . Comparison of results obtained with a rigid (thin lines) CNT to results obtained with a flexible (thick lines) CNT (top left, methane; top right, helium; bottom left, sulfur hexafluoride; and bottom right, a model fluid with the LJ diameter of helium and all other parameters as those of methane).

Image of FIG. 7.
FIG. 7.

(Color online) Self-diffusion coefficients of methane inside a (20,0) CNT at , obtained with different LA-IFC parameter sets (rigid CNT), compared to results obtained with a flexible CNT. The line is added to guide the eye.

Image of FIG. 8.
FIG. 8.

(Color online) Self-diffusion coefficients of methane inside a (20,0) CNT at , obtained with the fluid-solid thermal diffuse scattering algorithm, compared to results obtained with the LA-IFC thermostat. The lines are added to guide the eye.

Image of FIG. 9.
FIG. 9.

(Color online) Self-diffusion coefficients of helium inside a (20,0) CNT at , calculated with a flexible CNT, with a rigid nanotube, and with different LA-IFC parameter sets. The lines are added to guide the eye.

Image of FIG. 10.
FIG. 10.

(Color online) Self-diffusion coefficients of methane inside a (20,0) CNT at various temperatures, calculated with the LA-IFC thermostat, compared to results obtained with a flexible CNT. The lines are added to guide the eye.

Image of FIG. 11.
FIG. 11.

(Color online) Self-diffusion coefficients of methane inside various CNTs at , calculated with the LA-IFC thermostat, compared to results obtained with a flexible CNT. The lines are added to guide the eye.

Tables

Generic image for table
Table I.

Self-diffusion coefficients at zero loading inside a (20,0) CNT at . Errors are given in the subscripts.

Generic image for table
Table II.

Parameter sets for the LA-IFC thermostat.

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/content/aip/journal/jcp/124/15/10.1063/1.2185619
2006-04-18
2014-04-19
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: A novel algorithm to model the influence of host lattice flexibility in molecular dynamics simulations: Loading dependence of self-diffusion in carbon nanotubes
http://aip.metastore.ingenta.com/content/aip/journal/jcp/124/15/10.1063/1.2185619
10.1063/1.2185619
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