137 research outputs found

### Phase Separation and Aggregation in Multiblock Chains

This article focuses on phase and aggregation behavior for linear chains
composed of blocks of hydrophilic and hydrophobic segments. Phase and
conformational transitions of patterned chains are relevant for understanding
liquid-liquid separation of biomolecular condensates, which play a prominent
role in cellular biophysics, but also for surfactant and polymer applications.
Previous studies of simple models for multiblock chains have shown that,
depending on the sequence pattern and chain length, such systems can fall into
one of two categories: displaying either phase separation or aggregation into
finite-size clusters. The key new result of the present study is that both
formation of finite-size aggregates and phase separation can be observed for
certain chain architectures at appropriate conditions of temperature and
concentration. For such systems, a bulk dense liquid condenses from a dilute
phase that already contains multi-chain finite-size aggregates. The
computational approach involves several distinct steps using
histogram-reweighting grand canonical Monte Carlo simulations, which are
described here in some level of detail.Comment: 9 pages, 11 figure

### Shear induced ordering in systems with competing interactions: A machine learning study

When short-range attractions are combined with long-range repulsions in
colloidal particle systems, complex microphases can emerge. Here, we study a
system of isotropic particles which can form lamellar structures or a
disordered fluid phase when temperature is varied. We show that at equilibrium
the lamellar structure crystallizes, while out of equilibrium the system forms
a variety of structures at different shear rates and temperatures above
melting. The shear-induced ordering is analyzed by means of principal component
analysis and artificial neural networks, which are applied to data of reduced
dimensionality. Our results reveal the possibility of inducing ordering by
shear, potentially providing a feasible route to the fabrication of ordered
lamellar structures from isotropic particles.Comment: The following article has been accepted by the Journal of Chemical
Physics AIP. After it is published, it will be found at
https://aip.scitation.org/journal/jc

### The heat capacity of the restricted primitive model electrolyte

The constant-volume heat capacity, C_V(T, rho), of the restricted primitive
model (RPM) electrolyte is considered in the vicinity of its critical point. It
is demonstrated that, despite claims, recent simulations for finite systems do
not convincingly indicate the absence of a divergence in C_V(T, rho)--which
would point to non-Ising-type criticality. The strong qualitative difference
between C_V for the RPM and for a Lennard-Jones fluid is shown to result from
the low critical density of the former. If one considers the theoretically
preferable configurational heat-capacity density, C_V/V, the finite-size
results for the two systems display qualitatively similar behavior on
near-critical isotherms.Comment: 5 Pages, including 5 EPS figures. Also available as PDF file at
http://pallas.umd.edu/~luijten/erikpubs.htm

### Phase Equilibria of Lattice Polymers from Histogram Reweighting Monte Carlo Simulations

Histogram-reweighting Monte Carlo simulations were used to obtain polymer /
solvent phase diagrams for lattice homopolymers of chain lengths up to r=1000
monomers. The simulation technique was based on performing a series of grand
canonical Monte Carlo calculations for a small number of state points and
combining the results to obtain the phase behavior of a system over a range of
temperatures and densities. Critical parameters were determined from
mixed-field finite-size scaling concepts by matching the order parameter
distribution near the critical point to the distribution for the
three-dimensional Ising universality class. Calculations for the simple cubic
lattice (coordination number z=6) and for a high coordination number version of
the same lattice (z=26) were performed for chain lengths significantly longer
than in previous simulation studies. The critical temperature was found to
scale with chain length following the Flory-Huggins functional form. For the
z=6 lattice, the extrapolated infinite chain length critical temperature is
3.70+-0.01, in excellent agreement with previous calculations of the
temperature at which the osmotic second virial coefficient is zero and the mean
end-to-end distance proportional to the number of bonds. This confirms that the
three alternative definitions of the Theta-temperature are equivalent in the
limit of long chains. The critical volume fraction scales with chain length
with an exponent equal to 0.38+-0.01, in agreement with experimental data but
in disagreement with polymer solution theories. The width of the coexistence
curve prefactor was tentatively found to scale with chain length with an
exponent of 0.20+-0.03 for z = 6 and 0.22+-0.03 for z = 26. These values are
near the lower range of values obtained from experimental data.Comment: 23 pages, including 7 figure

### Coarse Grained Computations for a Micellar System

We establish, through coarse-grained computation, a connection between
traditional, continuum numerical algorithms (initial value problems as well as
fixed point algorithms) and atomistic simulations of the Larson model of
micelle formation. The procedure hinges on the (expected) evolution of a few
slow, coarse-grained mesoscopic observables of the MC simulation, and on
(computational) time scale separation between these and the remaining "slaved",
fast variables. Short bursts of appropriately initialized atomistic simulation
are used to estimate the (coarse-grained, deterministic) local dynamics of the
evolution of the observables. These estimates are then in turn used to
accelerate the evolution to computational stationarity through traditional
continuum algorithms (forward Euler integration, Newton-Raphson fixed point
computation). This "equation-free" framework, bypassing the derivation of
explicit, closed equations for the observables (e.g. equations of state) may
provide a computational bridge between direct atomistic / stochastic simulation
and the analysis of its macroscopic, system-level consequences

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