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Origin of the yield stress anomaly in L12 intermetallics unveiled with physically-informed machine-learning potentials

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arxiv 2406.04948 v1 pith:SWZT5TQS submitted 2024-06-07 cond-mat.mtrl-sci

Origin of the yield stress anomaly in L12 intermetallics unveiled with physically-informed machine-learning potentials

classification cond-mat.mtrl-sci
keywords intermetallicsstressunlockinganomalyyielddislocationformationmachine-learning
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The yield stress anomaly of L12 intermetallics such as Ni3Al or Ni3Ga is controlled by the so-called Kear-Wilsdorf lock (KWL), of which the formation and unlocking are governed by dislocation cross-slip. Despite the importance of L12 intermetallics for strengthening Ni-based superalloys, microscopic understanding of the KWL is limited. Here, molecular dynamics simulations are conducted by employing a dedicated machine-learning interatomic potential derived via physically-informed active-learning. The potential facilitates modelling of the dislocation behavior in Ni3Al with near ab initio accuracy. KWL formation and unlocking are observed and analyzed. The unlocking stress demonstrates a pronounced temperature dependence, contradicting the assumptions of existing analytical models. A phenomenological model is proposed to effectively describe the atomistic unlocking stresses and extrapolate them to the macroscopic scale. The model is general and applicable to other L12 intermetallics. The acquired knowledge of KWLs provides a deeper understanding on the origin of the yield stress anomaly.

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