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Numerical simulation of Gaussian chains near hard surfaces
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View: Figures


Image of FIG. 1.
FIG. 1.

Density profiles across a slit for a polymer melt with different contour discretization . The points show results obtained from MC simulations and the line is the theoretical prediction from the ground-state dominance of SCFT, Eq. (11). The slit width is and the other parameters are: , , and . Also shown is the profile obtained without the correction given by Eq. (6) for a polymer melt having a contour discretization .

Image of FIG. 2.
FIG. 2.

Density profiles of a melt confined in a slit of width , for various compressibility parameters . The chain discretization is and the other parameters are the same as in Fig. 1. The circles are the results obtained for the MC simulation; the lines show the analytical predictions from Eq. (11).

Image of FIG. 3.
FIG. 3.

Density profiles across the slit for a polymer solution with for an interaction range (triangles) or (squares). The third curve (circles) corresponds to a higher solution concentration with . The chain discretization is in all cases. The line is the theoretical predictions from Eq. (11).

Image of FIG. 4.
FIG. 4.

Exponential of the effective bonded potential between beads associated to Eq. (7) in the vicinity of a nanoparticle with radius . The two beads have a radial coordinate and and the angle between their position vector is . From left to right, is fixed to . The continuous lines are the corresponding un-normalized Gaussian curves.

Image of FIG. 5.
FIG. 5.

Density profile around one spherical nanoparticle with radius . Circles are obtained using the effective bonded potential for , , and . Also shown are the results obtained without correction for (squares) and (triangles); the lines are guides to the eye.


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Numerical simulation of Gaussian chains near hard surfaces