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.
Jolliffe ,\ @noop title Principal component analysis (2nd edition) \ ( publisher Springer Verlag ,\ address Berlin ,\ year 2002 ) NoStop
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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.