• Journal of the Korean Electrochemical Society
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• v.5 no.2
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• pp.86-92
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• 2002

The present article is concerned with the application of the kinetic Monte Carlo simulation to electrochemistry of lithium intercalation from the kinetic view point. Basic concepts of the kinetic Monte Carlo method and the transition state theory were first introduced, and then the simulation procedures were explained to evaluate diffusion process. Finally the kinetic Monte Carlo method based upon the transition state theory was employed under the cell-impedance-controlled constraint to analyse the current transient and the linear sweep voltammogram for the $LiMn_2O_4$ electrode, one of the intercalation compounds. From the results, it was found that the kinetic Monte Carlo method is much relevant to investigate kinetics of the lithium intercalation in the field of electrochemistry.

• Journal of the Korean Chemical Society
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• v.62 no.3
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• pp.191-202
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• 2018

The aim of this work is to study Monte Carlo simulation of ethylene (co)polymerization over Ziegler-Natta catalyst as investigated by Chen et al. The results revealed that the Monte Carlo simulation was similar to sum square error (SSE) model to prediction of stage II and III of polymerization. In the case of activation stage (stage I) both model had slightly deviation from experimental results. The modeling results demonstrated that in homopolymerization, SSE was superior to predict polymerization rate in current stage while for copolymerization, Monte Carlo had preferable prediction. The Monte Carlo simulation approved the SSE results to determine role of each site in total polymerization rate and revealed that homopolymerization rate changed from site to site and order of center was different compared to copolymerization. The polymer yield was reduced by addition of hydrogen amount however there was no specific effect on uptake curve which was predicted by Monte Carlo simulation with good accuracy. In the case of copolymerization it was evolved that monomer chain length and monomer concentration influenced the rate of polymerization as rate of polymerization reduced from 1-hexene to 1-octene and increased when monomer concentration proliferate.

• Journal of the Korean Vacuum Society
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• v.9 no.4
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• pp.419-427
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• 2000

We propose a method to obtain various diffusion parameters of deposited atom. By comparing the results of kinetic Mote Carlo (KMC) simulation with the results of STM, HRLEED experiments, we can determine diffusion parameters including the hopping barrier of an adatom on terrace, detachment barrier at the step edge, and well known Schwoebel barrier. It is found that the branch-width, island density, and roughness were suitable atomic scale structure parameters for comparing simulation calculation with experimental results, and especially, it is found that the parameter branch-width which is not widely used in thin film growth study, plays an important role in determining diffusion barriers.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.811-816
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• 2022

This work presents the methodology used to expand the capabilities of the Monte Carlo code OpenMC for the calculation of reactor kinetic parameters: effective delayed neutron fraction β_eff and neutron generation time L. The modified code, OpenMC(Time-Dependent) or OpenMC(TD), was then used to calculate the effective delayed neutron fraction by using the prompt method, while the neutron generation time was estimated using the pulsed method, fitting Λ to the decay of the neutron population. OpenMC(TD) is intended to serve as an alternative for the estimation of kinetic parameters when licensed codes are not available. The results obtained are compared to experimental data and MCNP calculated values for 18 benchmark configurations.

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.731-734
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• 2003

An atomistic process modeling, Kinetic Monte Carlo simulation, has the advantage of being both conceptually simple and extremely powerful. Instead of diffusion equations, it is based on the definitions of the interactions between individual atoms and defects. Those interactions can be derived either directly from molecular dynamics, first principles calculations, or from experiment. In this paper, as a simple illustration of the kinetic Monte Carlo we simulate defects (self-interstitials and vacancies) diffusion after ion implantation in Si crystalline.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2165-2170
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• 2007

At nanoscales, the Boltzmann transport equation (BTE) can best describe the behavior of phonons which are energy carriers in crystalline materials. Through this study, the phonon transport in some micro/nanoscale problems was simulated with the Monte Carlo method which is a kind of the stochastic approach to the BTE. In the Monte Carlo method, the superparticles of which the number is the weighted value to the actual number of phonons are allowed to drift and be scattered by other ones based on the scattering probability. Accounting for the phonon dispersion relation and polarizations, we have confirmed the one-dimensional transient phonon transport in ballistic and diffusion limits, respectively. The thermal conductivity for GaAs was also calculated from the kinetic theory by using the proposed model. Besides, we simulated the electrostatic discharge event in the NMOS transistor as a two-dimensional problem by applying the Monte Carlo method.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.45-48
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• 2011

In this paper, vacancy clustering formation and diffusion of germanium substrate was studied. The analysis method was adopted Monte Carlo method. At temperatures higher than melting point, fewer clusters formed, but there was less variation in the number of clusters than at lower temperatures, as the time increased. Equilibrium diffusivities in the clustering region were $10^2$ lower than those of free vacancies in the initial stage of kinetic lattice Monte Carlo simulations. They were expressed according to three temperature regimes: at temperatures above 1,100 K, at temperatures of 1,100-900 K, and at temperatures below 900 K. The effective mean migration energy, 1.1 eV, closely coincided with that of the 1.0-1.2 eV in experiments.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.6
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• pp.25-31
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• 2004

In this paper, we introduce kinetic Monte Carlo (kMC) methods for simulating diffusion process in nano-scale device fabrication. At first, we review kMC theory and backgrounds and give a simple point defect diffusion process modeling in thermal annealing after ion (electron) implantation into Si crystalline substrate to help understand kinetic Monte Carlo methods. kMC is a kind of Monte Carlo but can simulate time evolution of diffusion process through Poisson probabilistic process. In kMC diffusion process, instead of. solving differential reaction-diffusion equations via conventional finite difference or element methods, it is based on a series of chemical reaction (between atoms and/or defects) or diffusion events according to event rates of all possible events. Every event has its own event rate and time evolution of semiconductor diffusion process is directly simulated. Those event rates can be derived either directly from molecular dynamics (MD) or first-principles (ab-initio) calculations, or from experimental data.

• Journal of the Korean Vacuum Society
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• v.21 no.2
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• pp.86-92
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• 2012

We have studied the effect of speed of deposited atom on morphology evolution during Glancing Angle Deposition (GLAD). Using Kinetic Monte Carlo simulation that incorporate molecular dynamics simulations, we have shown that the rough surface morphology became smoother as the speed of deposited atom is increased. The growth exponent ${\beta}$ change from 0.97 to 0.67 as the speed increase from ${\upsilon}_0$ to $10{\upsilon}_0$ in the case of GLAD. We also examined the effect of speed of deposited atom for the case of chemical vapor deposition (CVD) simulation. Compared to GLAD, the variation in scaling exponent ${\beta}$ is small but the speed of deposited atom also have considerable effect on growth morpholgy in the case of CVD.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.2
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• pp.187-193
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• 2009

Dynamic response of an elastic pendulum system under random excitations was studied by using the Lagrangian equations of motion which uses the kinetic and potential energy of a target system. The responses of random excitations were calculated by using Monte Carl simulation which uses the series of random numbers. The procedure of Monte Carlo simulation is generation of random numbers, system model, system output, and statistical management of output. When the levels of random excitations were changed, the expected responses of the pendulum system showed various responses.