Riccardo Mazzarello
(Department of Physics, Sapienza University of Rome)

Abstract:

Phase-change materials (PCMs) are an important family of alloys employed in non-volatile memories and neuromorphic devices. These devices exploit the ability of PCMs to undergo rapid and reversible transitions between crystalline and amorphous phases at high temperature. At ambient conditions, both phases are very stable. These properties imply a strong temperature dependence of the crystallization kinetics, which is attributed to the high fragility of the supercooled liquid phase. In this work, we conduct molecular dynamics simulations based on a neural network potential to investigate the potential energy landscape of liquid GeTe, a prototypical PCM. We also compute the configurational entropy as a function of temperature in the deeply supercooled regime. We also calculate the viscosity and the relaxation times in the same temperature range. Finally, we use the Adam-Gibbs equation to extrapolate the data down to the glass transition temperature and estimate the fragility.