scholarly journals Locally activated Monte Carlo method for long-time-scale simulations

2000 ◽  
Vol 61 (2) ◽  
pp. 980-987 ◽  
Author(s):  
M. Kaukonen ◽  
J. Peräjoki ◽  
R. M. Nieminen ◽  
G. Jungnickel ◽  
Th. Frauenheim
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Time Scale ◽  
Long Time

scholarly journals Simulations of long time scale dynamics using the dimer method

2001 ◽  
Vol 677 ◽  
Author(s):  
Graeme Henkelman ◽  
Hannes Jónsson
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Transition State ◽  
Time Scale ◽  
Transition State Theory ◽  
Kinetic Monte Carlo ◽  
Chem Phys ◽  
State Theory ◽  
Kinetic Monte Carlo Method ◽  
Long Time

We have carried out long time scale simulations where the “dimer method” [G. Henkelman and H. Jónsson, J. Chem. Phys. 111, 7010 (1999)] is used to find the mechanism and estimate the rate of transitions within harmonic transition state theory and time is evolved by using the kinetic Monte Carlo method. Unlike traditional applications of kinetic Monte Carlo, the atoms are not assigned to lattice sites and a list of all possible transitions does not need to be specified beforehand. Rather, the relevant transitions are found on the y during the simulation. An application to the diffusion and island formation of Al adatoms on an Al(100) surface is presented.

Simulation of Atomistic Crystal Growth from the Vapor Phase

1986 ◽  
Vol 77 ◽  
Author(s):  
Paul A. Taylor ◽  
Brian W. Dodson
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Crystal Growth ◽  
Monte Carlo Method ◽  
Vapor Phase ◽  
Time Scale ◽  
Transient Dynamics ◽  
Strained Layer ◽  
The Monte Carlo Method ◽  
Long Time

ABSTRACTWe are in the process of studying strained-layer growth of two-dimensional Lennard-Jones lattices. To do so, we have developed three techniques, based on the Monte Carlo method and molecular dynamics, of simulating atomistic crystal growth from the vapor phase. The Monte Carlo method efficiently simulates the effects of long time-scale processes on the growth of strained-layer systems, but omits the transient dynamics of particle adsorption. The second technique, using molecular dynamics, gives results suggesting that epitaxial growth of strained-layer systems can occur on the picosecond timescales. However, this technique cannot capture the influence of the long time-scale processes on the growth process. In view of the shortcomings of the previous two techniques, A hybrid technique incorporating both the Monte Carlo method and molecular dynamics, has been developed. In principle, this technique models the transient dynamics of adsorption as well as the long term evolution of the system. This technique, however, is limited by artifacts that may only be eliminated by use of unwarrented amounts of supercomputer time.

Geometry entrapment in Walk-on-Subdomains

2019 ◽  
Vol 25 (4) ◽  
pp. 329-340 ◽  
Author(s):  
Preston Hamlin ◽  
W. John Thrasher ◽  
Walid Keyrouz ◽  
Michael Mascagni
Keyword(s):  
Monte Carlo ◽  
Boltzmann Equation ◽  
Monte Carlo Method ◽  
Electrostatic Energy ◽  
Potential Solution ◽  
Long Time ◽  
Poisson Boltzmann ◽  
Poisson Boltzmann Equation ◽  
Monte Carlo Implementation

Abstract One method of computing the electrostatic energy of a biomolecule in a solution uses a continuum representation of the solution via the Poisson–Boltzmann equation. This can be solved in many ways, and we consider a Monte Carlo method of our design that combines the Walk-on-Spheres and Walk-on-Subdomains algorithms. In the course of examining the Monte Carlo implementation of this method, an issue was discovered in the Walk-on-Subdomains portion of the algorithm which caused the algorithm to sometimes take an abnormally long time to complete. As the problem occurs when a walker repeatedly oscillates between two subdomains, it is something that could cause a large increase in runtime for any method that used a similar algorithm. This issue is described in detail and a potential solution is examined.

scholarly journals Uniform-acceptance force-bias Monte Carlo method with time scale to study solid-state diffusion

2012 ◽  
Vol 85 (13) ◽  
Author(s):  
Maarten J. Mees ◽  
Geoffrey Pourtois ◽  
Erik C. Neyts ◽  
Barend J. Thijsse ◽  
André Stesmans
Keyword(s):  
Monte Carlo ◽  
Solid State ◽  
Monte Carlo Method ◽  
Time Scale ◽  
Solid State Diffusion ◽  
State Diffusion

scholarly journals A derivation and scalable implementation of the synchronous parallel kinetic Monte Carlo method for simulating long-time dynamics

2017 ◽  
Vol 219 ◽  
pp. 246-254 ◽  
Author(s):  
Hye Suk Byun ◽  
Mohamed Y. El-Naggar ◽  
Rajiv K. Kalia ◽  
Aiichiro Nakano ◽  
Priya Vashishta
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Kinetic Monte Carlo ◽  
Kinetic Monte Carlo Method ◽  
Time Dynamics ◽  
Long Time ◽  
Long Time Dynamics
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