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
2021 ◽  
Vol 29 ◽  
pp. 117-142
Author(s):  
Steffen Grieshammer ◽  
Sebastian Eisele

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.


2013 ◽  
Vol 753 ◽  
pp. 367-372
Author(s):  
Tae Wook Na ◽  
Chang Soo Park ◽  
Hyung Seok Shim ◽  
Byeong Joo Lee ◽  
Chan Hee Han ◽  
...  

Three-dimensional Monte Carlo simulations with real grain orientations are performed to study the role of precipitates and sub-boundaries in the abnormal grain growth. According to the simulation results, sub-boundaries in the abnormally growing grain and precipitates in the matrix grains are necessary for the abnormal grain growth. The simulation results can be best explained by the mechanism of sub-boundary enhanced solid state wetting. The simulated microstructure is very similar to that experimentally observed.


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