9 research outputs found
Generalized Gradient Approximation Made Thermal
Using the methodology of conditional-probability density functional theory,
and several mild assumptions, we calculate the temperature-dependence of the
Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA). This
numerically-defined thermal GGA reduces to the local approximation in the
uniform limit and PBE at zero temperature, and can be fit reasonably accurately
(within 8%) assuming the temperature-dependent enhancement is independent of
the gradient. This locally thermal PBE satisfies both the coordinate-scaled
correlation inequality and the concavity condition, which we prove for finite
temperatures. The temperature dependence differs markedly from existing thermal
GGA's.Comment: 6 pages, 5 figure
Effects of topological solitons on autocorrelation functions for chains of coupled torsional oscillators
©1983 American Institute of PhysicsThe electronic version of this article is the complete one and can be found online at: http://link.aip.org/link/?JCPSA6/78/6914/1DOI:10.1063/1.444640Brownian dynamics computer simulations were performed on chains of coupled torsional oscillators. The purpose was to observe the changes in autocorrelation functions, related to typical experimental measurements, caused by the introduction of topological solitons or kinks into the system. We considered three model systems: a chain of coupled torsional oscillators, a chain of coupled torsional oscillators with additional onefold rotational potentials acting on each oscillator, and a chain of coupled torsional oscillators with additional threefold rotational potentials. These models are of interest because of their application to torsional motions in polymeric systems, and, in particular, the system with onefold rotational potentials has been studied extensively as the sine–Gordon chain. We present simulation results for three autocorrelation functions of these three systems both with and without topological solitons
Correlation energy of the uniform gas determined by ground state conditional probability density functional theory
Conditional-probability density functional theory (CP-DFT) is a formally
exact method for finding correlation energies from Kohn-Sham DFT without
evaluating an explicit energy functional. We present details on how to generate
accurate exchange-correlation energies for the ground-state uniform gas. We
also use the exchange hole in a CP antiparallel spin calculation to extract the
high-density limit. We give a highly accurate analytic solution to the
Thomas-Fermi model for this problem, showing its performance relative to
Kohn-Sham and may be useful at high temperatures. We explore several
approximations to the CP potential. Results are compared to accurate
parameterizations for both exchange-correlation energies and holes.Comment: Corrected typos, minor changes in text and notation for clarity and
continuity with other work, results unchange
Topologically Induced Glass Transition in Freely Rotating Rods
We present a simple minimal model which allows numerical and analytical study of a glass transition. This is a model of rigid rods with fixed centers of rotation. The rods can rotate freely but cannot cross each other. The ratio of the length of the rods to the distance between the centers of rotation is the only parameter of this model. With increasing we observed a sharp crossover to practically infinite relaxation times in 2D arrays of rods. In 3D we found a real transition to a completely frozen random state at
Modeling the Transport of Nanoparticle-Filled Binary Fluids through Micropores
Understanding the transport of multicomponent fluids
through porous
medium is of great importance for a number of technological applications,
ranging from ink jet printing and the production of textiles to enhanced
oil recovery. The process of capillary filling is relatively well
understood for a single-component fluid; much less attention, however,
has been devoted to investigating capillary filling processes that
involve multiphase fluids, and especially nanoparticle-filled fluids.
Here, we examine the behavior of binary fluids containing nanoparticles
that are driven by capillary forces to fill well-defined pores or
microchannels. To carry out these studies, we use a hybrid computational
approach that combines the lattice Boltzmann model for binary fluids
with a Brownian dynamics model for the nanoparticles. This hybrid
approach allows us to capture the interactions among the fluids, nanoparticles,
and pore walls. We show that the nanoparticles can dynamically alter
the interfacial tension between the two fluids and the contact angle
at the pore walls; this, in turn, strongly affects the dynamics of
the capillary filling. We demonstrate that by tailoring the wetting
properties of the nanoparticles, one can effectively control the filling
velocities. Our findings provide fundamental insights into the dynamics
of this complex multicomponent system, as well as potential guidelines
for a number of technological processes that involve capillary filling
with nanoparticles in porous media