Berlin 2024 – wissenschaftliches Programm
Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe
MM: Fachverband Metall- und Materialphysik
MM 38: Mechanical Properties and Alloy Design: e.g. Light-Weight, High-Temperature, Multicomponent Materials III (joint session MM/KFM)
MM 38.3: Vortrag
Mittwoch, 20. März 2024, 12:15–12:30, C 230
Investigating the yield stress anomaly of Ni3Al with physically informed machine-learning potential — •Xiang Xu, Xi Zhang, Siegfried Schmauder, and Blazej Grabowski — University of Stuttgart, Stuttgart, Germany
The anomalously increasing yield stress with temperature of some intermetallics is predominately controlled by the Kear-Wilsdorf lock (KWL), of which the formation and unlocking are closely related to a cross-slip process. Yet so far, knowledge of this cross-lip process is limited, leading to significant approximations in existing models for predicting the mechanical behavior of those materials. In this study, molecular dynamics simulations were conducted by using a physically informed machine-learning potential to replicate dislocation activities of Ni3Al. For the first time, it is observed that the formation and unlocking of KWL occurs with a step-by-step cross-slip process, of which the distance varies between one or two atomic planes inside each step. Moreover, a strong temperature dependence of the necessary stress to unlock a KWL was discovered, differing from previous approximations. This study not only advances the understanding on the yield stress anomaly in Ni3Al, and also establishes a systematic workflow for yielding multiscale atomistic simulations using machine-learning potentials.
Keywords: Yield stress anomaly; Cross-slip; Kear-Wilsdorf lock; Machine-learning potentials; Molecular dynamics simulations