scholarly journals A Hybrid Molecular Dynamics Kinetic Monte Carlo Simulation Methodology

2021 ◽  
Author(s):  
◽  
Peter A. Zoontjens
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Grain Boundaries ◽  
Hybrid Model ◽  
Kinetic Monte Carlo ◽  
Computational Cost ◽  
Dynamics Simulation ◽  
Embedded Atom ◽  
Wide Range ◽  
Hybrid Methodology

<p>This thesis describes a novel hybrid computational methodology in which the Molecular Dynamics and Kinetic Monte Carlo methods are concurrently combined. This hybrid methodology has been developed to simulate phenomena which are unfeasible to treat with either Molecular Dynamics or Kinetic Monte Carlo alone, due to the wide range of time scales involved and the need for highly detailed atom dynamics. Is is shown that the hybrid methodology can reproduce the results of a larger (more atoms) all Molecular Dynamics simulation at a significant reduction in computational cost (run time) - due to the replacement of Molecular Dynamics atoms with Kinetic Monte Carlo atoms. The hybrid methodology has been successfully used to study the dynamics of epitaxial stacking fault grain boundaries. This work identified that grain boundary motion was hindered by atoms lodging in off-lattice sites, and also by overlayer islands built up by adatom deposition. It was verified that the ‘kink flip” move is a key element in the motion of grain boundaries. Methods for enhancing the hybrid methodology were researched. It was shown that by an optimal choice of damping parameter γ, wave reflections back into the Molecular Dynamics domain could be minimised. This is expected to enable the hybrid methodology to operate successfully with smaller Molecular Dynamics domains, making larger and/or longer simulation runs feasible. This research included the derivation of the dispersion relation for the discrete case with damping and net reflectivity formulas. These are believed to be new results. The hybrid model can be applied to a wide variety of MD and KMC methods. Other MD potentials such as Embedded Atom or Modified Embedded Atom could be employed. The KMC component can be developed to use a more refined lattice or an ”on the fly” KMC method could be employed. Both the MD and KMC components can be extended to handle more than one species of atom. Parallelised versions of the MD and KMC components could also be developed. Any situation where the problem can be decomposed into distinct domains of fine scale and coarse scale modelling respectively, is potentially suitable for treatment with a hybrid model of this design.</p>

scholarly journals A Hybrid Molecular Dynamics Kinetic Monte Carlo Simulation Methodology

2021 ◽  
Author(s):  
◽  
Peter A. Zoontjens
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Grain Boundaries ◽  
Hybrid Model ◽  
Kinetic Monte Carlo ◽  
Computational Cost ◽  
Dynamics Simulation ◽  
Embedded Atom ◽  
Wide Range ◽  
Hybrid Methodology

<p>This thesis describes a novel hybrid computational methodology in which the Molecular Dynamics and Kinetic Monte Carlo methods are concurrently combined. This hybrid methodology has been developed to simulate phenomena which are unfeasible to treat with either Molecular Dynamics or Kinetic Monte Carlo alone, due to the wide range of time scales involved and the need for highly detailed atom dynamics. Is is shown that the hybrid methodology can reproduce the results of a larger (more atoms) all Molecular Dynamics simulation at a significant reduction in computational cost (run time) - due to the replacement of Molecular Dynamics atoms with Kinetic Monte Carlo atoms. The hybrid methodology has been successfully used to study the dynamics of epitaxial stacking fault grain boundaries. This work identified that grain boundary motion was hindered by atoms lodging in off-lattice sites, and also by overlayer islands built up by adatom deposition. It was verified that the ‘kink flip” move is a key element in the motion of grain boundaries. Methods for enhancing the hybrid methodology were researched. It was shown that by an optimal choice of damping parameter γ, wave reflections back into the Molecular Dynamics domain could be minimised. This is expected to enable the hybrid methodology to operate successfully with smaller Molecular Dynamics domains, making larger and/or longer simulation runs feasible. This research included the derivation of the dispersion relation for the discrete case with damping and net reflectivity formulas. These are believed to be new results. The hybrid model can be applied to a wide variety of MD and KMC methods. Other MD potentials such as Embedded Atom or Modified Embedded Atom could be employed. The KMC component can be developed to use a more refined lattice or an ”on the fly” KMC method could be employed. Both the MD and KMC components can be extended to handle more than one species of atom. Parallelised versions of the MD and KMC components could also be developed. Any situation where the problem can be decomposed into distinct domains of fine scale and coarse scale modelling respectively, is potentially suitable for treatment with a hybrid model of this design.</p>

scholarly journals Theoretical Analysis and Atomistic Modelling of Diffusion and Stability of Pure Element Hollow Nanospheres and Nanotubes

2008 ◽  
Vol 277 ◽  
pp. 21-26 ◽  
Author(s):  
Alexander V. Evteev ◽  
Elena V. Levchenko ◽  
Irina V. Belova ◽  
Graeme E. Murch
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Middle Part ◽  
Dynamics Simulation ◽  
Vacancy Mechanism ◽  
Pure Element ◽  
Hollow Nanosphere ◽  
Analytical Analysis ◽  
Atomistic Modelling

A theoretical and atomistic study of diffusion and stability of a pure element hollow nanosphere and nanotube is performed. The shrinkage via the vacancy mechanism of these hollow nano-objects is described analytically. Using Gibbs-Thomson boundary conditions an exact solution of the kinetic equation in quasi steady-state at the linear approximation is obtained. The collapse time as a function of the geometrical sizes of the hollow nano-objects is determined. Kinetic Monte Carlo simulation of the shrinkage of these nano-objects is performed: it confirms the predictions of the analytical analysis. Next, molecular dynamics simulation in combination with the embedded atom method is used to investigate diffusion by the vacancy mechanism in a Pd hollow nanosphere and nanotube. It is found that the diffusion coefficient in a Pd hollow nanosphere and nanotube is larger near the inner and external surfaces compared with the middle part of a nanoshell. The molecular dynamics results provide quite a strong but indirect argument that a real pure element hollow nanosphere and nanotube may not shrink as readily via the vacancy mechanism as compared with the predictions of the analytical analysis and kinetic Monte Carlo simulations.

Combined Kinetic Monte Carlo—Molecular Dynamics Approach for Modeling Phonon Transport in Quantum Dot Superlattices

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Neil Zuckerman ◽  
Jennifer R. Lukes
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Quantum Dot ◽  
Cross Sections ◽  
Kinetic Monte Carlo ◽  
Detailed Balance ◽  
Phonon Transport ◽  
Dynamics Simulation ◽  
Base Layer ◽  
Phase Functions

A new kinetic Monte Carlo method for modeling phonon transport in quantum dot superlattices is presented. The method uses phonon scattering phase functions and cross sections to describe collisions between phonons and quantum dots. The phase functions and cross sections are generated using molecular dynamics simulation, which is capable of including atomistic effects otherwise unavailable in Monte Carlo approaches. The method is demonstrated for a test case featuring a Si-Ge quantum dot superlattice, and the model is compared against published experiments. It is found that molecular dynamics-derived cross sections must be weighted by diffuse mismatch model-type weighting factors in order to satisfy detailed balance considerations. Additionally, it is found that thin alloy “base layer” films strongly reduce thermal conductivity in these systems and must be included in the modeling to obtain agreement with published experimental data.

Bayesian active learning of interatomic force field for molecular dynamics simulation of Pt/Ag(111)

2021 ◽  
Author(s):  
Kai Xu ◽  
Lei Yan ◽  
Bingran You
Keyword(s):  
Molecular Dynamics ◽  
Active Learning ◽  
Force Field ◽  
Density Functional ◽  
Process Model ◽  
Large Scale ◽  
Computational Cost ◽  
Dynamics Simulation ◽  
Potential Energy Landscape ◽  
Three Body

Force field is a central requirement in molecular dynamics (MD) simulation for accurate description of the potential energy landscape and the time evolution of individual atomic motions. Most energy models are limited by a fundamental tradeoff between accuracy and speed. Although ab initio MD based on density functional theory (DFT) has high accuracy, its high computational cost prevents its use for large-scale and long-timescale simulations. Here, we use Bayesian active learning to construct a Gaussian process model of interatomic forces to describe Pt deposited on Ag(111). An accurate model is obtained within one day of wall time after selecting only 126 atomic environments based on two- and three-body interactions, providing mean absolute errors of 52 and 142 meV/Å for Ag and Pt, respectively. Our work highlights automated and minimalistic training of machine-learning force fields with high fidelity to DFT, which would enable large-scale and long-timescale simulations of alloy surfaces at first-principles accuracy.

Coarse kMC-based replica exchange algorithms for the accelerated simulation of protein folding in explicit solvent

2016 ◽  
Vol 18 (18) ◽  
pp. 13052-13065 ◽  
Author(s):  
Emanuel K. Peter ◽  
Joan-Emma Shea ◽  
Igor V. Pivkin
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Protein Folding ◽  
Kinetic Monte Carlo ◽  
Replica Exchange ◽  
Replica Exchange Molecular Dynamics ◽  
Accelerated Simulation ◽  
Explicit Solvent ◽  
Exchange Algorithms

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC).

Molecular Dynamics Simulation of Sputtering with Mmany-Body Interactions

1988 ◽  
Vol 100 ◽  
Author(s):  
Davy Y. Lo ◽  
Tom A. Tombrello ◽  
Mark H. Shapiro ◽  
Don E. Harrison
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Single Crystal ◽  
Low Energy ◽  
Dynamics Simulation ◽  
Embedded Atom Method ◽  
Many Body ◽  
Embedded Atom ◽  
Dynamics Simulations ◽  
Small Single Crystal

ABSTRACTMany-body forces obtained by the Embedded-Atom Method (EAM) [41 are incorporated into the description of low energy collisions and surface ejection processes in molecular dynamics simulations of sputtering from metal targets. Bombardments of small, single crystal Cu targets (400–500 atoms) in three different orientations ({100}, {110}, {111}) by 5 keV Ar+ ions have been simulated. The results are compared to simulations using purely pair-wise additive interactions. Significant differences in the spectra of ejected atoms are found.

scholarly journals A method to construct the dynamic landscape of a bio-membrane with experiment and simulation

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Albert A. Smith ◽  
Alexander Vogel ◽  
Oskar Engberg ◽  
Peter W. Hildebrand ◽  
Daniel Huster
Keyword(s):  
Molecular Dynamics ◽  
Nmr Relaxation ◽  
Dynamics Simulation ◽  
Comprehensive Description ◽  
Correlation Times ◽  
Wide Range ◽  
Dynamic Landscape ◽  
C Nmr ◽  
Analysis Of Motion

AbstractBiomolecular function is based on a complex hierarchy of molecular motions. While biophysical methods can reveal details of specific motions, a concept for the comprehensive description of molecular dynamics over a wide range of correlation times has been unattainable. Here, we report an approach to construct the dynamic landscape of biomolecules, which describes the aggregate influence of multiple motions acting on various timescales and on multiple positions in the molecule. To this end, we use 13C NMR relaxation and molecular dynamics simulation data for the characterization of fully hydrated palmitoyl-oleoyl-phosphatidylcholine bilayers. We combine dynamics detector methodology with a new frame analysis of motion that yields site-specific amplitudes of motion, separated both by type and timescale of motion. In this study, we show that this separation allows the detailed description of the dynamic landscape, which yields vast differences in motional amplitudes and correlation times depending on molecular position.

scholarly journals Computational Prediction of Heteromeric Protein Complex Disassembly Order with Hybrid Monte Carlo/Molecular Dynamics Simulation

2022 ◽  
Author(s):  
Ikuo Kurisaki ◽  
Shigenori Tanaka
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Protein Complex ◽  
Protein Complexes ◽  
Structural Bioinformatics ◽  
Dynamics Simulation ◽  
Tryptophan Synthase ◽  
Selection Scheme ◽  
Hybrid Monte Carlo ◽  
Multimeric Protein

The physicochemical entity of biological phenomenon in the cell is a network of biochemical reactions and the activity of such a network is regulated by multimeric protein complexes. Mass spectroscopy (MS) experiments and multimeric protein docking simulations based on structural bioinformatics techniques have revealed the molecular-level stoichiometry and static configuration of subcomplexes in their bound forms, then revealing the subcomplex populations and formation orders. Meanwhile, these methodologies are not designed to straightforwardly examine temporal dynamics of multimeric protein assembly and disassembly, essential physicochemical properties to understand functional expression mechanisms of proteins in the biological environment. To address the problem, we had developed an atomistic simulation in the framework of the hybrid Monte Carlo/Molecular Dynamics (hMC/MD) method and succeeded in observing disassembly of homomeric pentamer of the serum amyloid P component protein in experimentally consistent order. In this study, we improved the hMC/MD method to examine disassembly processes of the tryptophan synthase tetramer, a paradigmatic heteromeric protein complex in MS studies. We employed the likelihood-based selection scheme to determine a dissociation-prone subunit pair at each hMC/MD simulation cycle and achieved highly reliable predictions of the disassembly orders with the success rate over 0.9 without a priori knowledge of the MS experiments and structural bioinformatics simulations. We similarly succeeded in reliable predictions for the other three tetrameric protein complexes. These achievements indicate the potential availability of our hMC/MD approach as the general purpose methodology to obtain microscopic and physicochemical insights into multimeric protein complex formation.

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