dc.description.abstract
In soft matter systems, one often is confronted with macromolecular objects dissolved in
a fluid. Usually, the particles that make up the latter are significantly smaller and lighter
than the macromolecules. This in turn induces that the two components have different
time- (e.g. typical relaxation times), length-, or mass-scales which might differ by several
orders of magnitude.
As such, atomistic simulations of large ensembles are sometimes prohibitively expensive.
Given the disparity in the aforementioned scales, one possibility to deal with this issue is
to neglect the solvent; however, one needs to take particular care along that route not to
distort, or entirely lose access to, those phenomena that are characteristic for soft matter
systems, which often arise from the very interplay between the two types of components.
One such prominent phenomenon is that of viscoelasticity, or non-Newtonian flow, where
the viscosity of the solute-solvent-mixture depends on the local shear stress. We present
a generalization [1, 2, 3] of the mesoscopic Multiparticle Collision Dynamics (MPC) al-
gorithm [4, 5], which enables simulations of large systems of macromolecules dissolved
in an effective, but explicit, solvent. This allows the solvent to mediate hydrodynamic
interactions in a computationally highly efficient way.
The extension presented amounts to linking effective solvent particles via harmonic po-
tentials to form coarse-grained polymers; their elastic degrees of freedom give rise to
shear-dependent phenomena. The resulting MPC fluid is, given a suitable degree of
polymerization, tantamount to a simplified model of a polymer melt, and exhibits intrinsic
viscoelastic behavior. This enables MPC studies of other dissolved particles, such as
colloids, in inherently non-Newtonian solvents.
We discuss the relationship between system parameters (i.e., the length of the effec-
tive polymers and interaction strength), and characteristic properties of the system. In
particular, we focus on the velocity autocorrelation function in Fourier-space, C̃ v T (k, t) =
h ṽ (k, t) · ṽ (k, 0)i. From the analysis of this function we are able to extract information on
a wide spectrum of properties, such as viscosity, diffusion behavior, polymer relaxation
times, and the rheology in the long-time limit. We present an analytic (Rouse-based)
formalism that allows one to calculate within suitable approximations C̃ v T ; this framework
offers the possibility to efficiently tune the input parameters to match desired characteris-
tic features in the correlation function. An excellent qualitative and quantitative agreement
of the theoretical predictions and the simulation data can be reported.
[1]
[2]
[3]
[4]
[5]
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B. Kowalik and R. G. Winkler, J. Chem. Phys. 138, 104903 (2013).
D. Toneian, Diploma Thesis, TU Wien (2015).
A. Malevanets and R. Kapral, J. Chem. Phys. 110, 8605 (1999).
G. Gompper, T. Ihle, D. M. Kroll, and R. G. Winkler, Adv. Polym. Sci. 221, 1 (2009).
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