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.

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.

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>

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).

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.

scholarly journals Chemo-mechanical coupling in kerogen gas adsorption/desorption

2018 ◽  
Vol 20 (18) ◽  
pp. 12390-12395 ◽  
Author(s):  
Tuan Anh Ho ◽  
Yifeng Wang ◽  
Louise J. Criscenti
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Molecular Dynamics Simulation ◽  
Simulation Study ◽  
Gas Adsorption ◽  
Dynamics Simulation ◽  
Hybrid Monte Carlo ◽  
Mechanical Coupling ◽  
Adsorption Desorption

Strong chemo-mechanical coupling in kerogen gas adsorption from a hybrid Monte Carlo/molecular dynamics simulation study.

L1 Regularization-Based Model Reduction of Complex Chemistry Molecular Dynamics for Statistical Learning of Kinetic Monte Carlo Models

MRS Advances ◽  
2016 ◽  
Vol 1 (24) ◽  
pp. 1767-1772 ◽  
Author(s):  
Qian Yang ◽  
Carlos A. Sing-Long ◽  
Evan J. Reed
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
A Priori ◽  
Reaction Network ◽  
Md Simulations ◽  
Rate Coefficients ◽  
Elementary Reactions ◽  
L1 Regularization ◽  
Complex Chemistry

ABSTRACTKinetic Monte Carlo (KMC) methods have been a successful technique for accelerating time scales and increasing system sizes beyond those achievable with fully atomistic simulations. However, a requirement for its success is a priori knowledge of all relevant reaction pathways and their rate coefficients. This can be difficult for systems with complex chemistry, such as shock-compressed materials at high temperatures and pressures or phenolic spacecraft heat shields undergoing pyrolysis, which can consist of hundreds of molecular species and thousands of distinct reactions. In this work, we develop a method for first estimating a KMC model composed of elementary reactions and rate coefficients by using large datasets derived from a few molecular dynamics (MD) simulations of shock compressed liquid methane, and then using L1 regularization to reduce the estimated chemical reaction network. We find that the full network of 2613 reactions can be reduced by 89% while incurring approximately 9% error in the dominant species (CH4) population. We find that the degree of sparsity achievable decreases when similar accuracy is required for additional populations of species.

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