Efficient 3D Kinetic Monte Carlo Method for Modeling of Molecular Structure and Dynamics

Mikhail Panshenskov, Ilia Solov'yov, Andrey V. Solov'yov

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

Self-assembly of molecular systems is an important and general problem that intertwines physics, chemistry, biology, and material sciences. Through understanding of the physical principles of self-organization, it often becomes feasible to control the process and to obtain complex structures with tailored properties, for example, bacteria colonies of cells or nanodevices with desired properties. Theoretical studies and simulations provide an important tool for unraveling the principles of self-organization and, therefore, have recently gained an increasing interest. The present article features an extension of a popular code MBN EXPLORER (MesoBioNano Explorer) aiming to provide a universal approach to study self-assembly phenomena in biology and nanoscience. In particular, this extension involves a highly parallelized module of MBN EXPLORER that allows simulating stochastic processes using the kinetic Monte Carlo approach in a three-dimensional space. We describe the computational side of the developed code, discuss its efficiency, and apply it for studying an exemplary system.
OriginalsprogEngelsk
TidsskriftJournal of Computational Chemistry
Vol/bind35
Sider (fra-til)1317-1329
Antal sider13
ISSN0192-8651
DOI
StatusUdgivet - 2014

Fingeraftryk

Kinetic Monte Carlo
Self-assembly
Self-organization
Monte Carlo method
Self assembly
Molecular structure
Biology
Molecular dynamics
Monte Carlo methods
Nanoscience
Kinetics
Materials Science
Materials science
Random processes
Complex Structure
Modeling
Bacteria
Chemistry
Stochastic Processes
Physics

Citer dette

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abstract = "Self-assembly of molecular systems is an important and general problem that intertwines physics, chemistry, biology, and material sciences. Through understanding of the physical principles of self-organization, it often becomes feasible to control the process and to obtain complex structures with tailored properties, for example, bacteria colonies of cells or nanodevices with desired properties. Theoretical studies and simulations provide an important tool for unraveling the principles of self-organization and, therefore, have recently gained an increasing interest. The present article features an extension of a popular code MBN EXPLORER (MesoBioNano Explorer) aiming to provide a universal approach to study self-assembly phenomena in biology and nanoscience. In particular, this extension involves a highly parallelized module of MBN EXPLORER that allows simulating stochastic processes using the kinetic Monte Carlo approach in a three-dimensional space. We describe the computational side of the developed code, discuss its efficiency, and apply it for studying an exemplary system.",
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Efficient 3D Kinetic Monte Carlo Method for Modeling of Molecular Structure and Dynamics. / Panshenskov, Mikhail; Solov'yov, Ilia; Solov'yov, Andrey V.

I: Journal of Computational Chemistry, Bind 35, 2014, s. 1317-1329.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Efficient 3D Kinetic Monte Carlo Method for Modeling of Molecular Structure and Dynamics

AU - Panshenskov, Mikhail

AU - Solov'yov, Ilia

AU - Solov'yov, Andrey V.

PY - 2014

Y1 - 2014

N2 - Self-assembly of molecular systems is an important and general problem that intertwines physics, chemistry, biology, and material sciences. Through understanding of the physical principles of self-organization, it often becomes feasible to control the process and to obtain complex structures with tailored properties, for example, bacteria colonies of cells or nanodevices with desired properties. Theoretical studies and simulations provide an important tool for unraveling the principles of self-organization and, therefore, have recently gained an increasing interest. The present article features an extension of a popular code MBN EXPLORER (MesoBioNano Explorer) aiming to provide a universal approach to study self-assembly phenomena in biology and nanoscience. In particular, this extension involves a highly parallelized module of MBN EXPLORER that allows simulating stochastic processes using the kinetic Monte Carlo approach in a three-dimensional space. We describe the computational side of the developed code, discuss its efficiency, and apply it for studying an exemplary system.

AB - Self-assembly of molecular systems is an important and general problem that intertwines physics, chemistry, biology, and material sciences. Through understanding of the physical principles of self-organization, it often becomes feasible to control the process and to obtain complex structures with tailored properties, for example, bacteria colonies of cells or nanodevices with desired properties. Theoretical studies and simulations provide an important tool for unraveling the principles of self-organization and, therefore, have recently gained an increasing interest. The present article features an extension of a popular code MBN EXPLORER (MesoBioNano Explorer) aiming to provide a universal approach to study self-assembly phenomena in biology and nanoscience. In particular, this extension involves a highly parallelized module of MBN EXPLORER that allows simulating stochastic processes using the kinetic Monte Carlo approach in a three-dimensional space. We describe the computational side of the developed code, discuss its efficiency, and apply it for studying an exemplary system.

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