30 research outputs found
Molecular dynamics study of orientational order and rotational melting in clusters of TeF 6
Molecular dynamics simulations of the behavior of molecules in crystalline clusters of TeF 6 were carried out on systems of 100, 150, 250, and 350 molecules. Several diagnostic functions were applied to investigate whether rotational melting occurred before translational melting. These functions included the coefficient of rotational diffusion D Ξ ( T ), the âorientational Lindemann indexâ ÎŽ Ξ ( T ), the âorientational angular distribution functionâ Q (Ξ, T ), and the âorientational pair-correlation functionâ g Ξ ( r, T ). All indicators implied that rotational melting occurred before translational melting, that it began with the outermost molecules, and that its onset for smaller clusters was at lower temperatures than for larger clusters. Results also showed that the rotational transition coincided with the transition from a lower symmetry phase (monoclinic) to cubic, a phenomenon that had been noted by others to occur with some regularity for systems of globular molecules.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43961/1/10053_2005_Article_BF01426586.pd
Overlap Distribution of the Three-Dimensional Ising Model
We study the Parisi overlap probability density P_L(q) for the
three-dimensional Ising ferromagnet by means of Monte Carlo (MC) simulations.
At the critical point P_L(q) is peaked around q=0 in contrast with the double
peaked magnetic probability density. We give particular attention to the tails
of the overlap distribution at the critical point, which we control over up to
500 orders of magnitude by using the multi-overlap MC algorithm. Below the
critical temperature interface tension estimates from the overlap probability
density are given and their approach to the infinite volume limit appears to be
smoother than for estimates from the magnetization.Comment: 7 pages, RevTex, 9 Postscript figure
Surface critical behavior in fixed dimensions : Nonanalyticity of critical surface enhancement and massive field theory approach
The critical behavior of semi-infinite systems in fixed dimensions is
investigated theoretically. The appropriate extension of Parisi's massive field
theory approach is presented.Two-loop calculations and subsequent Pad\'e-Borel
analyses of surface critical exponents of the special and ordinary phase
transitions yield estimates in reasonable agreement with recent Monte Carlo
results. This includes the crossover exponent , for which we obtain
the values and , considerably
lower than the previous -expansion estimates.Comment: Latex with Revtex-Stylefiles, 4 page
Critical Behavior of the Ferromagnetic Ising Model on a Sierpinski Carpet: Monte Carlo Renormalization Group Study
We perform a Monte Carlo Renormalization Group analysis of the critical
behavior of the ferromagnetic Ising model on a Sierpi\'nski fractal with
Hausdorff dimension . This method is shown to be relevant to
the calculation of the critical temperature and the magnetic
eigen-exponent on such structures. On the other hand, scaling corrections
hinder the calculation of the temperature eigen-exponent . At last, the
results are shown to be consistent with a finite size scaling analysis.Comment: 16 pages, 7 figure
Monte Carlo Renormalization Group Analysis of Lattice Model in
We present a simple, sophisticated method to capture renormalization group
flow in Monte Carlo simulation, which provides important information of
critical phenomena. We applied the method to lattice model and
obtained renormalization flow diagram which well reproduces theoretically
predicted behavior of continuum model. We also show that the method
can be easily applied to much more complicated models, such as frustrated spin
models.Comment: 13 pages, revtex, 7 figures. v1:Submitted to PRE. v2:considerably
reduced redundancy of presentation. v3:final version to appear in Phys.Rev.
Algebraic Self-Similar Renormalization in Theory of Critical Phenomena
We consider the method of self-similar renormalization for calculating
critical temperatures and critical indices. A new optimized variant of the
method for an effective summation of asymptotic series is suggested and
illustrated by several different examples. The advantage of the method is in
combining simplicity with high accuracy.Comment: 1 file, 44 pages, RevTe
Monte Carlo Methods for Estimating Interfacial Free Energies and Line Tensions
Excess contributions to the free energy due to interfaces occur for many
problems encountered in the statistical physics of condensed matter when
coexistence between different phases is possible (e.g. wetting phenomena,
nucleation, crystal growth, etc.). This article reviews two methods to estimate
both interfacial free energies and line tensions by Monte Carlo simulations of
simple models, (e.g. the Ising model, a symmetrical binary Lennard-Jones fluid
exhibiting a miscibility gap, and a simple Lennard-Jones fluid). One method is
based on thermodynamic integration. This method is useful to study flat and
inclined interfaces for Ising lattices, allowing also the estimation of line
tensions of three-phase contact lines, when the interfaces meet walls (where
"surface fields" may act). A generalization to off-lattice systems is described
as well.
The second method is based on the sampling of the order parameter
distribution of the system throughout the two-phase coexistence region of the
model. Both the interface free energies of flat interfaces and of (spherical or
cylindrical) droplets (or bubbles) can be estimated, including also systems
with walls, where sphere-cap shaped wall-attached droplets occur. The
curvature-dependence of the interfacial free energy is discussed, and estimates
for the line tensions are compared to results from the thermodynamic
integration method. Basic limitations of all these methods are critically
discussed, and an outlook on other approaches is given
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genesâincluding reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)âin critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
Molecular dynamics simulation of the plastic to triclinic phase transition in clusters of SF6
Clusters of 512 SF6 molecules in their condensed phases are simulated by molecular dynamics on the DAP computers, using a Lennard-Jones rigid-molecule model. The results are presented in the form of orientational distribution plots (dot-plots) and powder diffraction patterns. As the clusters approach melting, the outermost two molecular layers appear to melt first. Cooling the melt gives rise only to a glassy phase. However, nucleation can be identified in a cluster being cooled from the plastic phase, showing that the growth of the true crystal is initiated in the inner regions of the cluster. The crystalline clusters form generally as polycrystals, often bi-crystals, and these can be classified in terms of three different types of pseudo-twins. Attempts to anneal these clusters to give perfect single crystals failed below 100 K, and even above 100 K annealing tended to produce the more stable forms of pseudo-twin. Smaller clusters of 128 molecules readily formed perfect single crystals ; the simulation of clusters substantially larger than 512 would be computationally very demanding.Une simulation de la dynamique moléculaire a été effectuée sur des agrégats de 512 molecules de SF6 à l'aide d'un modÚle de molécules rigides interagissant selon un potentiel atome-atome de Lennard-Jones. Les calculs ont été effectués sur les ordinateurs parallÚles DAP. Les résultats sont présentés sous la forme de diagrammes de distribution d'orientations et de spectres de diffraction. A haute température, les deux couches externes des globules fondent en premier. Lorsqu'un agrégat de la phase plastique est refroidi, une transition est observée vers la phase basse température, la nucléation s'effectuant à partir du centre. Les agrégats de la phase basse température sont généralement des cristaux doubles de différents types et qui sont parfois des macles ou pseudo-macles. Un recuit de ces cristaux vers 100 K conduit à la forme la plus stable de ces pseudo-macles. Ce phénomÚne n'est pas observé dans des agrégats de taille plus petite (128 molécules), ceux-ci formant des monocristaux. La simulation de plus gros agrégats n'a pas été entreprise