Hexagonal ice density dependence on inter atomic distance changes due to nuclear quantum effects
Lucas T. S. de Miranda, M\'arcio S. Gomes-Filho, Mariana Rossi, Luana S. Pedroza, Alexandre R. Rocha

TL;DR
This study uses machine learning potentials to analyze how nuclear quantum effects influence the density and interatomic interactions in hexagonal ice, revealing discrepancies with experimental data and the role of hydrogen bonds.
Contribution
It demonstrates the impact of nuclear quantum effects on ice density and interatomic interactions using machine learning potentials with various exchange-correlation functionals.
Findings
Most functionals overestimate ice density compared to experiments.
Quantum nuclear treatment further increases the discrepancy with experimental density.
Nuclear quantum effects strengthen hydrogen bonds in hexagonal ice.
Abstract
Hexagonal ice (), the most common structure of ice, displays a variety of fascinating properties. Despite major efforts, a theoretical description of all its properties is still lacking. In particular, correctly accounting for its density and interatomic interactions is of utmost importance as a stepping stone for a deeper understanding of other properties. Deep potentials are a recent alternative to investigate the properties of {\iceIH}, which aims to match the accuracy of \textit{ab initio} simulations with the simplicity and scalability of classical molecular dynamics. This becomes particularly significant if one wishes to address nuclear quantum effects. In this work, we use machine learning potentials obtained for different exchange and correlation functionals to simulate the structural and vibrational properties of {\iceIH}. We show that most functionals overestimate…
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Taxonomy
TopicsQuantum, superfluid, helium dynamics · Material Dynamics and Properties · Advanced Condensed Matter Physics
