Interatomic machine learning potentials for aluminium: application to solidification phenomena
@inproceedings{Jakse2022InteratomicML, title={Interatomic machine learning potentials for aluminium: application to solidification phenomena}, author={No{\"e}l Jakse and Johannes Sandberg and Leon F Granz and Anthony Saliou and Philippe Jarry and Emilie Devijver and Thomas Voigtmann and J{\"u}rgen Horbach and Andreas Meyer}, year={2022} }
In studying solidification process by simulations on the atomic scale, the modeling of crystal nucleation or amorphisation requires the construction of interatomic interactions that are able to reproduce the properties of both the solid and the liquid states. Taking into account rare nucleation events or structural relaxation under deep undercooling conditions requires much larger length scales and longer time scales than those achievable by ab initio molecular dynamics (AIMD). This problem is…
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