TY - BOOK
T1 - Stability and mobility of small and large Cu-vacancy clusters in FeCu alloys using an artificial intelligence driven atomistic kinetic Monte Carlo method
AU - Pascuet, Ines
AU - Malerba, Lorenzo
AU - Castin, Nicolas
A2 - Bonny, Giovanni
N1 - RN - ER-93
Score = 2
PY - 2009/5
Y1 - 2009/5
N2 - Information on point-defect cluster stability and mobility is needed in order to parameterise models describing the nanostructure evolution of reactor pressure vessel steels under irradiation, but cannot be obtained directly from experimental measurements. The stability and mobility of vacancy-containing copper clusters and precipitates in iron has been quantitatively studied using advanced atomistic kinetic Monte Carlo methods, whose physical reliability has been improved by employing artificial intelligence techniques for the regression of the activation energies required by the model as input. Thus, the model validation was based, on the one hand, on comparison with available ab-initio (quantum mechanical) calculation for the verification of the used cohesive model, and, on the other, with other models and theories. The direct validation on experimental studies of copper precipitation appears to be computationally challenging, due to space- and time-scale limitations of the model.
AB - Information on point-defect cluster stability and mobility is needed in order to parameterise models describing the nanostructure evolution of reactor pressure vessel steels under irradiation, but cannot be obtained directly from experimental measurements. The stability and mobility of vacancy-containing copper clusters and precipitates in iron has been quantitatively studied using advanced atomistic kinetic Monte Carlo methods, whose physical reliability has been improved by employing artificial intelligence techniques for the regression of the activation energies required by the model as input. Thus, the model validation was based, on the one hand, on comparison with available ab-initio (quantum mechanical) calculation for the verification of the used cohesive model, and, on the other, with other models and theories. The direct validation on experimental studies of copper precipitation appears to be computationally challenging, due to space- and time-scale limitations of the model.
KW - diffusivity Cu-vacancy clusters
KW - atomistic kinetic Monte Carlo
UR - http://ecm.sckcen.be/OTCS/llisapi.dll/open/ezp_101744
M3 - ER - External report
VL - 1
T3 - SCK•CEN Reports
BT - Stability and mobility of small and large Cu-vacancy clusters in FeCu alloys using an artificial intelligence driven atomistic kinetic Monte Carlo method
PB - SCK CEN
ER -