Melting Behavior and Phase Stability of CaO from Neural Network Potentials: a Molecular Dynamics Study
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 Tm=3055±11 K and Tm=2847±15 K, respectively.\\ We calculate an enthalpy of fusion of ΔHf∼73 kJ/mol, in agreement with thermodynamic assessments and ab initio calculations. We also reproduce the thermal expansion and obtain a volume increase of ∼29% at Tm, consistent with the corresponding decrease in density extracted from spatially resolved number density profiles. Finally, we calculate the high-pressure melting curve of CaO up to 20 GPa, providing one of the very few computational determinations of this quantity to date. The results confirm that the overheating ratio η is not constant under pressure, increasing from 17% at ambient pressure to 24% at 20 GPa, confirming previous findings and ruling out the assumption of a fixed overheating ratio. Our results establish MLIP-based simulations as a robust and efficient framework for investigating phase stability in ionic oxides and provide new insight into the melting behavior of CaO under extreme conditions.
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BibTeX
@misc{menescardi2026melting,
title = {{Melting Behavior and Phase Stability of CaO from Neural Network Potentials: a Molecular Dynamics Study}},
author = {Francesca Menescardi and Stefano de Gironcoli},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2605.14793},
eprint = {2605.14793},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.14793},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Melting Behavior and Phase Stability of CaO from Neural Network Potentials: a Molecular Dynamics Study
AU - Francesca Menescardi
AU - Stefano de Gironcoli
PY - 2026
DA - 2026/09/16
PB - arXiv
DO - 10.48550/arxiv.2605.14793
UR - https://arxiv.org/abs/2605.14793
AB - 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 T_m=3055±11 K and T_m=2847±15 K, respectively.\\ We calculate an enthalpy of fusion of ΔH_f∼73 kJ/mol, in agreement with thermodynamic assessments and ab initio calculations. We also reproduce the thermal expansion and obtain a volume increase of ∼29% at Tm, consistent with the corresponding decrease in density extracted from spatially resolved number density profiles. Finally, we calculate the high-pressure melting curve of CaO up to 20 GPa, providing one of the very few computational determinations of this quantity to date. The results confirm that the overheating ratio η is not constant under pressure, increasing from 17% at ambient pressure to 24% at 20 GPa, confirming previous findings and ruling out the assumption of a fixed overheating ratio. Our results establish MLIP-based simulations as a robust and efficient framework for investigating phase stability in ionic oxides and provide new insight into the melting behavior of CaO under extreme conditions.
ER -