Monte Carlo simulation of homopolymer chains. I. Second virial coefficient

2003 ◽  
Vol 118 (10) ◽  
pp. 4721-4732 ◽  
Author(s):  
Ian M. Withers ◽  
Andrey V. Dobrynin ◽  
Max L. Berkowitz ◽  
Michael Rubinstein
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Virial Coefficient ◽  
Second Virial Coefficient

scholarly journals THE FOURTH VIRIAL COEFFICIENT OF ANYONS

1998 ◽  
Vol 13 (21) ◽  
pp. 3723-3747 ◽  
Author(s):  
ANDERS KRISTOFFERSEN ◽  
STEFAN MASHKEVICH ◽  
JAN MYRHEM ◽  
KÅRE OLAUSSEN
Keyword(s):  
Monte Carlo ◽  
Fourier Series ◽  
Monte Carlo Method ◽  
Path Integral ◽  
Virial Coefficient ◽  
Path Integrals ◽  
Second Virial Coefficient ◽  
Virial Coefficients ◽  
Partition Functions ◽  
Two Dimensional

We have computed by a Monte Carlo method the fourth virial coefficient of free anyons, as a function of the statistics angle θ. It can be fitted by a four term Fourier series, in which two coefficients are fixed by the known perturbative results at the boson and fermion points. We compute partition functions by means of path integrals, which we represent diagramatically in such a way that the connected diagrams give the cluster coefficients. This provides a general proof that all cluster and virial coefficients are finite. We give explicit polynomial approximations for all path integral contributions to all cluster coefficients, implying that only the second virial coefficient is statistics dependent, as is the case for two-dimensional exclusion statistics. The assumption leading to these approximations is that the tree diagrams dominate and factorize.

Monte Carlo Study of the Second Virial Coefficient of Star Polymers in a Good Solvent

1996 ◽  
Vol 29 (6) ◽  
pp. 2269-2274 ◽  
Author(s):  
Kaoru Ohno ◽  
Kazuhito Shida ◽  
Masayuki Kimura ◽  
Yoshiyuki Kawazoe
Keyword(s):  
Monte Carlo ◽  
Virial Coefficient ◽  
Second Virial Coefficient ◽  
Star Polymers ◽  
Monte Carlo Study

scholarly journals A Monte Carlo study of the second virial coefficient of semiflexible ring polymers

2010 ◽  
Vol 42 (9) ◽  
pp. 735-744 ◽  
Author(s):  
Daichi Ida ◽  
Daisuke Nakatomi ◽  
Takenao Yoshizaki
Keyword(s):  
Monte Carlo ◽  
Virial Coefficient ◽  
Second Virial Coefficient ◽  
Monte Carlo Study ◽  
Ring Polymers

Monte Carlo calculation of the osmotic second virial coefficient of off-lattice athermal polymers

1992 ◽  
Vol 25 (15) ◽  
pp. 3979-3983 ◽  
Author(s):  
Arun Yethiraj ◽  
Kevin G. Honnell ◽  
Carol K. Hall
Keyword(s):  
Monte Carlo ◽  
Virial Coefficient ◽  
Monte Carlo Calculation ◽  
Second Virial Coefficient

Monte Carlo Study of the Second Virial Coefficient and Statistical Exponent of Star Polymers with Large Numbers of Branches

2000 ◽  
Vol 33 (20) ◽  
pp. 7655-7662 ◽  
Author(s):  
Kazuhito Shida ◽  
Kaoru Ohno ◽  
Masayuki Kimura ◽  
Yoshiyuki Kawazoe
Keyword(s):  
Monte Carlo ◽  
Virial Coefficient ◽  
Second Virial Coefficient ◽  
Star Polymers ◽  
Monte Carlo Study ◽  
Large Numbers

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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