Monte Carlo simulations of a liquid crystal copolymer in the solid state

1998 ◽  
Vol 36 (5) ◽  
pp. 727-741 ◽  
Author(s):  
Stephen H. Foulger ◽  
Gregory C. Rutledge
Keyword(s):  
Monte Carlo ◽  
Liquid Crystal ◽  
Solid State ◽  
Monte Carlo Simulations

scholarly journals Doping liquid crystals with nanoparticles. A computer simulation of the effects of nanoparticle shape

2016 ◽  
Vol 18 (4) ◽  
pp. 2428-2441 ◽  
Author(s):  
Silvia Orlandi ◽  
Erika Benini ◽  
Isabella Miglioli ◽  
Dean R. Evans ◽  
Victor Reshetnyak ◽  
...  
Keyword(s):  
Computer Simulation ◽  
Monte Carlo ◽  
Liquid Crystal ◽  
Liquid Crystals ◽  
Monte Carlo Simulations ◽  
Orientational Order ◽  
Nanoparticle Shape ◽  
Nanoparticle Dispersions ◽  
Molecular Scale ◽  
Clearing Temperature

Molecular-scale Monte Carlo simulations of liquid crystal-nanoparticle dispersions show the effect on the orientational order and on the clearing temperature of shape and concentration of the dopant nanoparticles.

Kinetic Monte Carlo Simulations for Solid State Ionics: Case Studies with the MOCASSIN Program

2021 ◽  
Vol 29 ◽  
pp. 117-142
Author(s):  
Steffen Grieshammer ◽  
Sebastian Eisele
Keyword(s):  
Monte Carlo ◽  
Solid State ◽  
Ionic Conductivity ◽  
Monte Carlo Simulations ◽  
Kinetic Monte Carlo ◽  
Model Systems ◽  
Solid State Ionics ◽  
Kinetic Monte Carlo Simulations ◽  
Defect Interactions ◽  
The Impact

Kinetic Monte Carlo simulations are a useful tool to predict and analyze the ionic conductivity in crystalline materials. We present here the basic functionalities and capabilities of our recently published Monte Carlo software for solid state ionics called MOCASSIN, exemplified by simulations of several model systems and real materials. We address the simulation of tracer correlation factors for various structures, the correlation in systems with complex migration mechanisms like interstitialcy or vehicle transport, and the impact of defect interactions on ionic conductivity. Simulations of real materials include a review of oxygen vacancy migration in doped ceria, oxygen interstitial migration in La-rich melilites, and proton conduction in acceptor doped fully hydrated barium zirconate. The results reveal the impact of defect interactions on the ionic conductivity and the importance of the defect distribution. Combinations of these effects can lead to unexpected transport behavior in solid state ionic materials, especially for multiple mobile species. Kinetic Monte Carlo simulations are therefore useful to interpret experimental data which shows unexpected behavior regarding the dependence on temperature and composition.

Implementation of correlated sampling method for Monte Carlo simulations of small-sized solid-state dosimetric response

2014 ◽  
Vol 30 ◽  
pp. e137-e138
Author(s):  
R. Wang ◽  
P. Pittet ◽  
G.-N. Lu ◽  
P. Guiral ◽  
A. Ahnesjö
Keyword(s):  
Monte Carlo ◽  
Solid State ◽  
Monte Carlo Simulations ◽  
Sampling Method ◽  
Correlated Sampling
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