Atomistic Kinetic Monte Carlo studies of microchemical evolutions driven by diffusion processes under irradiation

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Atomistic Kinetic Monte Carlo studies of microchemical evolutions driven by diffusion processes under irradiation. / Soisson, Frédéric; Becquart, Charlotte; Castin, Nicolas; Domain, Christophe; Malerba, Lorenzo; Vincent, Edwige; Terentyev, Dmitry (Peer reviewer); Bonny, Giovanni (Peer reviewer).

In: Journal of Nuclear Materials, Vol. 406, No. 1, 11.2010, p. 55-67.

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Soisson, Frédéric ; Becquart, Charlotte ; Castin, Nicolas ; Domain, Christophe ; Malerba, Lorenzo ; Vincent, Edwige ; Terentyev, Dmitry ; Bonny, Giovanni. / Atomistic Kinetic Monte Carlo studies of microchemical evolutions driven by diffusion processes under irradiation. In: Journal of Nuclear Materials. 2010 ; Vol. 406, No. 1. pp. 55-67.

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@article{5a66a9a61877448c9da3cdc7c08ef32f,
title = "Atomistic Kinetic Monte Carlo studies of microchemical evolutions driven by diffusion processes under irradiation",
abstract = "Atomistic Kinetic Monte Carlo (AKMC) simulations are a powerful tool to study the microstructural and microchemical evolution of alloys controlled by diffusion processes, under irradiation and during thermal ageing. In the framework of the FP6 Perfect program, two main approaches have been applied to binary and multicomponent iron based alloys. The first one is based on a diffusion model which takes into account vacancy and self-interstitial jumps, using simple rigid lattice approximation and broken-bond models to compute the point-defect jump frequencies. The corresponding parameters are fitted on ab initio calculations of a few typical configurations and migration barriers. The second method uses empirical potentials to compute a much larger number of migration barriers, including atomic relaxations, and Artificial Intelligence regression methods to predict the other ones. It is somewhat less rapid than the first one, but significantly more than simulations using ‘‘on-the-fly” calculations of all the barriers. We review here the recent advances and perspectives concerning these techniques.",
keywords = "atomistic kinetic Monte Carlo, artificial intelligence",
author = "Fr{\'e}d{\'e}ric Soisson and Charlotte Becquart and Nicolas Castin and Christophe Domain and Lorenzo Malerba and Edwige Vincent and Dmitry Terentyev and Giovanni Bonny",
note = "Score = 10",
year = "2010",
month = "11",
doi = "10.1016/j.jnucmat.2010.05.018",
language = "English",
volume = "406",
pages = "55--67",
journal = "Journal of Nuclear Materials",
issn = "0022-3115",
publisher = "Elsevier",
number = "1",

}

RIS - Download

TY - JOUR

T1 - Atomistic Kinetic Monte Carlo studies of microchemical evolutions driven by diffusion processes under irradiation

AU - Soisson, Frédéric

AU - Becquart, Charlotte

AU - Castin, Nicolas

AU - Domain, Christophe

AU - Malerba, Lorenzo

AU - Vincent, Edwige

A2 - Terentyev, Dmitry

A2 - Bonny, Giovanni

N1 - Score = 10

PY - 2010/11

Y1 - 2010/11

N2 - Atomistic Kinetic Monte Carlo (AKMC) simulations are a powerful tool to study the microstructural and microchemical evolution of alloys controlled by diffusion processes, under irradiation and during thermal ageing. In the framework of the FP6 Perfect program, two main approaches have been applied to binary and multicomponent iron based alloys. The first one is based on a diffusion model which takes into account vacancy and self-interstitial jumps, using simple rigid lattice approximation and broken-bond models to compute the point-defect jump frequencies. The corresponding parameters are fitted on ab initio calculations of a few typical configurations and migration barriers. The second method uses empirical potentials to compute a much larger number of migration barriers, including atomic relaxations, and Artificial Intelligence regression methods to predict the other ones. It is somewhat less rapid than the first one, but significantly more than simulations using ‘‘on-the-fly” calculations of all the barriers. We review here the recent advances and perspectives concerning these techniques.

AB - Atomistic Kinetic Monte Carlo (AKMC) simulations are a powerful tool to study the microstructural and microchemical evolution of alloys controlled by diffusion processes, under irradiation and during thermal ageing. In the framework of the FP6 Perfect program, two main approaches have been applied to binary and multicomponent iron based alloys. The first one is based on a diffusion model which takes into account vacancy and self-interstitial jumps, using simple rigid lattice approximation and broken-bond models to compute the point-defect jump frequencies. The corresponding parameters are fitted on ab initio calculations of a few typical configurations and migration barriers. The second method uses empirical potentials to compute a much larger number of migration barriers, including atomic relaxations, and Artificial Intelligence regression methods to predict the other ones. It is somewhat less rapid than the first one, but significantly more than simulations using ‘‘on-the-fly” calculations of all the barriers. We review here the recent advances and perspectives concerning these techniques.

KW - atomistic kinetic Monte Carlo

KW - artificial intelligence

UR - http://ecm.sckcen.be/OTCS/llisapi.dll/open/ezp_108516

UR - http://knowledgecentre.sckcen.be/so2/bibref/7253

U2 - 10.1016/j.jnucmat.2010.05.018

DO - 10.1016/j.jnucmat.2010.05.018

M3 - Article

VL - 406

SP - 55

EP - 67

JO - Journal of Nuclear Materials

JF - Journal of Nuclear Materials

SN - 0022-3115

IS - 1

ER -

ID: 242745