A machine-learning interatomic potential fitted to DFT data simulates ns-scale crystallization and phase separation in Ge-rich GeSbTe alloys at 600 K, producing metastable cubic GeTe and amorphous GeSb/Ge phases.
Zhang , author J
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On phase separation and crystallization of Ge-rich GeSbTe alloys from atomistic simulations with a machine learning interatomic potential
A machine-learning interatomic potential fitted to DFT data simulates ns-scale crystallization and phase separation in Ge-rich GeSbTe alloys at 600 K, producing metastable cubic GeTe and amorphous GeSb/Ge phases.