Temperature dependent stacking fault free energy profiles and partial dislocation separation in FCC Cu

Autor: Reza Namakian, Dorel Moldovan, Thomas D. Swinburne
Přispěvatelé: Louisiana State University (LSU), Centre National de la Recherche Scientifique (CNRS), Centre Interdisciplinaire de Nanoscience de Marseille (CINaM), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), ANR-19-CE46-0006,MeMoPAS,Mesoscale models from massively parallel atomistic simulations: uncertainty driven, self-optimizing strategies for hard materials(2019)
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Computational Materials Science
Computational Materials Science, 2023, 218, pp.111971. ⟨10.1016/j.commatsci.2022.111971⟩
ISSN: 0927-0256
Popis: International audience; The generalized stacking fault energy profile is fundamental to models of metal plasticity and thus a key parameter for alloy design. However, to account for thermal vibrations, models require the stacking fault free energy profile, but current methods can only calculate metastable intrinsic stacking faults. We show how the full stacking fault free energy profile can be calculated using PAFI, a linear scaling method that fully accounts for anharmonic thermal vibrations. Applying our approach to empirical and machine learning potentials for FCC Cu, we show via direct comparison with molecular dynamics simulations that accounting for temperature effects is essential to predict the statistics of partial dislocation separations. The machine learning potential gives quantitative agreement with available density functional theory data on the intrinsic stacking fault energy, whilst additionally returning the unstable stacking fault, a key parameter for predicting ductile fracture.
Databáze: OpenAIRE
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