The set of known stable phases of water may not be complete, and some of the phase boundaries between them are fuzzy. Starting from liquid water and a comprehensive set of 50 ice structures, we compute the phase diagram at three hybrid density-functional-theory levels of approximation, accounting for thermal and nuclear fluctuations as well as proton disorder. Such calculations are only made tractable because we combine machine-learning methods and advanced free-energy techniques. The computed phase diagram is in qualitative agreement with experiment, particularly at pressures ≲ 8000 bar, and the discrepancy in chemical potential is comparable with the subtle uncertainties introduced by proton disorder and the spread between the three hybri...
International audienceDespite the simplicity of its molecular unit, water is a challenging system be...
Water ice is a unique material, presenting the most complex phase diagram known in the literature, r...
We show how machine learning techniques based on Bayesian inference can be used to reach new levels ...
Funder: CSCS Swiss National Supercomuputing Centre (project s957)Abstract: The set of known stable p...
Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted ...
We provide DFT input files, example ice configurations studied, a Mathematica notebook used to colla...
Water is one of the most abundant molecules on Earth. However, this common and “simple” material has...
7 pags, 6 figs, 1 tabThe phase diagram of water has been calculated from the TIP4PQ/2005 model, an e...
First published September 25, 2017.Water is vital to our everyday life, but its structure at a molec...
All the different phases of water ice between 2 GPa and several megabars are based on a single body-...
Most water in the universe may be superionic, and its thermodynamic and transport properties are cru...
Predictive modelling and quantitative understanding of nucleation is essential for predicting phase ...
Density functional theory (DFT) has been extensively used to model the properties of water. Albeit m...
Water molecules can arrange into a liquid with complex hydrogen-bond networks and at least 17 experi...
Abstract: Water molecules can arrange into a liquid with complex hydrogen-bond networks and at least...
International audienceDespite the simplicity of its molecular unit, water is a challenging system be...
Water ice is a unique material, presenting the most complex phase diagram known in the literature, r...
We show how machine learning techniques based on Bayesian inference can be used to reach new levels ...
Funder: CSCS Swiss National Supercomuputing Centre (project s957)Abstract: The set of known stable p...
Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted ...
We provide DFT input files, example ice configurations studied, a Mathematica notebook used to colla...
Water is one of the most abundant molecules on Earth. However, this common and “simple” material has...
7 pags, 6 figs, 1 tabThe phase diagram of water has been calculated from the TIP4PQ/2005 model, an e...
First published September 25, 2017.Water is vital to our everyday life, but its structure at a molec...
All the different phases of water ice between 2 GPa and several megabars are based on a single body-...
Most water in the universe may be superionic, and its thermodynamic and transport properties are cru...
Predictive modelling and quantitative understanding of nucleation is essential for predicting phase ...
Density functional theory (DFT) has been extensively used to model the properties of water. Albeit m...
Water molecules can arrange into a liquid with complex hydrogen-bond networks and at least 17 experi...
Abstract: Water molecules can arrange into a liquid with complex hydrogen-bond networks and at least...
International audienceDespite the simplicity of its molecular unit, water is a challenging system be...
Water ice is a unique material, presenting the most complex phase diagram known in the literature, r...
We show how machine learning techniques based on Bayesian inference can be used to reach new levels ...