Melting Behavior and Phase Stability of CaO from Neural Network Potentials: a Molecular Dynamics Study
Francesca Menescardi, Stefano de Gironcoli

TL;DR
This study develops a machine learning interatomic potential for CaO, enabling large-scale molecular dynamics simulations to accurately determine its melting behavior and phase stability under various conditions, including high pressure.
Contribution
The paper introduces a new MLIP for CaO trained on ab initio data, allowing precise simulations of melting behavior and phase stability under extreme conditions.
Findings
Melting temperature at ambient pressure is approximately 2900-3055 K.
Calculated enthalpy of fusion is about 73 kJ/mol, aligning with previous assessments.
High-pressure melting curve up to 20 GPa is provided, showing the overheating ratio increases with pressure.
Abstract
We investigate the melting behavior of calcium oxide (CaO) under extreme conditions, a problem that remains poorly constrained due to experimental limitations despite its relevance for geophysical and technological applications. We develop a Machine Learning Interatomic Potential (MLIP) for CaO with PANNA 2.0 and the LATTE descriptor, training it on a dataset of 12,000 configurations including solid, liquid, interfacial, and void-containing structures, extracted from ab-initio molecular dynamics data employing PBEsol exchange-correlation functional. We perform large-scale molecular dynamics simulations to compute the melting temperature at ambient pressure using both the void-nucleated melting (VNM) and two-phase coexistence (TPC) methods, obtaining K and K, respectively.\\ We calculate an enthalpy of fusion of kJ/mol, in…
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