Comment on “Monte Carlo simulations of smectic phase transitions in flexible-rigid-flexible molecules” [J. Chem. Phys. 110, 12183 (1999)]

1999 ◽  
Vol 111 (19) ◽  
pp. 9113-9113
Author(s):  
B. M. Fung ◽  
Thomas Bräuniger
Keyword(s):  
Monte Carlo ◽  
Phase Transitions ◽  
Monte Carlo Simulations ◽  
Chem Phys ◽  
Smectic Phase ◽  
Flexible Molecules

Acceleration Algorithms in Monte Carlo Simulations in Statistical Physics

1991 ◽  
Vol 02 (01) ◽  
pp. 201-208
Author(s):  
ROBERT H. SWENDSEN
Keyword(s):  
Monte Carlo ◽  
Phase Transitions ◽  
Monte Carlo Simulations ◽  
Statistical Physics ◽  
Relaxation Times ◽  
Critical Slowing Down ◽  
Cluster Approach ◽  
New Developments ◽  
Slowing Down ◽  
Thermodynamic Phase

Monte Carlo simulations of thermodynamic phase transitions are usually hampered by long relaxation times due to the phenomenon of “critical slowing down.” Using a mapping due to Fortuin and Kasteleyn, a cluster approach to Monte Carlo simulations has been developed, which greatly reduces relaxation times, improving efficiency by up to two or three orders of magnitude. New developments and extensions of this approach are also discussed.

Self-assembly of conformationally flexible molecules under 2D confinement: structural analysis from computer simulations

2018 ◽  
Vol 54 (63) ◽  
pp. 8749-8752 ◽  
Author(s):  
Damian Nieckarz ◽  
Paweł Szabelski
Keyword(s):  
Monte Carlo ◽  
Structural Analysis ◽  
Monte Carlo Simulations ◽  
Computer Simulations ◽  
Self Assembly ◽  
Flexible Molecules

Monte Carlo simulations reveal the role of surface conformers in self-assembly on crystalline supports.

Phase transitions of single polymer chains and of polymer solutions: insights from Monte Carlo simulations

2008 ◽  
Vol 20 (49) ◽  
pp. 494215 ◽  
Author(s):  
K Binder ◽  
W Paul ◽  
T Strauch ◽  
F Rampf ◽  
V Ivanov ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Phase Transitions ◽  
Monte Carlo Simulations ◽  
Polymer Solutions ◽  
Polymer Chains

Superficial Phase Transitions in Nanoalloys

2011 ◽  
Vol 172-174 ◽  
pp. 658-663 ◽  
Author(s):  
Mohamed Briki ◽  
Jérôme Creuze ◽  
Fabienne Berthier ◽  
Bernard Legrand
Keyword(s):  
Phase Diagram ◽  
Monte Carlo ◽  
Phase Transitions ◽  
Monte Carlo Simulations ◽  
Bimetallic Nanoparticles ◽  
Bimodal Distribution ◽  
The Other ◽  
Nanoparticle Assembly ◽  
Interatomic Potentials ◽  
Grand Canonical

In order to build the phase diagram of Cu-Ag nanoalloys, we study a 405-atom nanoparticle by means of Monte Carlo simulations with relaxations usingN-body interatomic potentials. We focus on a range of nominal concentrations for which the cluster core remains Cu-pure and the (001) facets of the outer shell exhibit two original phenomena. Within the (N,mAg-mCu,P,T) ensemble, a structural and chemical bistability is observed, which affects all the (001) facets together. For a nanoparticle assembly, this will result in a bimodal distribution of clusters, some of them having their (001) facets Cu-rich with the usual square shape, the other ones having their (001) facets Ag-rich with a diamond shape. This bistability is replaced in the (NAg,NCu,P,T) ensemble by a continuous evolution of both the structure and the concentration of the (001) facets from Cu-rich square-shaped to Ag-rich diamond-shaped facets as the number of Ag atoms increases. For a nanoparticle assembly, this will result in an unimodal distribution of the cluster population concerning the properties of the (001) facets. This comparison between pseudo grand canonical and isothermal-isobaric results shows that the distribution of a population of bimetallic nanoparticles depends strongly on the conditions under it is elaborated.

scholarly journals Monte Carlo simulations of the γ–β, α–γ, and α–β phase transitions of nitrogen

1997 ◽  
Vol 106 (21) ◽  
pp. 8806-8813 ◽  
Author(s):  
A. Mulder ◽  
J. P. J. Michels ◽  
J. A. Schouten
Keyword(s):  
Monte Carlo ◽  
Phase Transitions ◽  
Monte Carlo Simulations ◽  
Β Phase
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