Although liquid water is ubiquitous in chemical reactions at roots of life and climate on the earth, the prediction of its properties by high-level ab initio molecular dynamics simulations still represents a formidable task for quantum chemistry. In this article, we present a room temperature simulation of liquid water based on the potential energy surface obtained by a many-body wave function through quantum Monte Carlo (QMC) methods. The simulated properties are in good agreement with recent neutron scattering and X-ray experiments, particularly concerning the position of the oxygen-oxygen peak in the radial distribution function, at variance of previous density functional theory attempts. Given the excellent performances of QMC on large scale supercomputers, this work opens new perspectives for predictive and reliable ab initio simulations of complex chemical systems.

Ab initio molecular dynamics simulation of liquid water by quantum Monte Carlo / Zen, Andrea; Luo, Ye; Mazzola, Guglielmo; Guidoni, Leonardo; Sorella, Sandro. - In: THE JOURNAL OF CHEMICAL PHYSICS. - ISSN 0021-9606. - 142:14(2015), pp. 1-14. [10.1063/1.4917171]

Ab initio molecular dynamics simulation of liquid water by quantum Monte Carlo

Zen, Andrea;Luo, Ye;Mazzola, Guglielmo;Guidoni, Leonardo;Sorella, Sandro
2015-01-01

Abstract

Although liquid water is ubiquitous in chemical reactions at roots of life and climate on the earth, the prediction of its properties by high-level ab initio molecular dynamics simulations still represents a formidable task for quantum chemistry. In this article, we present a room temperature simulation of liquid water based on the potential energy surface obtained by a many-body wave function through quantum Monte Carlo (QMC) methods. The simulated properties are in good agreement with recent neutron scattering and X-ray experiments, particularly concerning the position of the oxygen-oxygen peak in the radial distribution function, at variance of previous density functional theory attempts. Given the excellent performances of QMC on large scale supercomputers, this work opens new perspectives for predictive and reliable ab initio simulations of complex chemical systems.
2015
142
14
1
14
144111
https://arxiv.org/abs/1412.2936
Zen, Andrea; Luo, Ye; Mazzola, Guglielmo; Guidoni, Leonardo; Sorella, Sandro
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/14803
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