MP2 provides a good description of hydrogen bonding in water clusters and includes longrange dispersion interactions without the need to introduce empirical elements in the description of the interatomic potential. To assess its performance for bulk liquid water under ambient conditions, an isobaric-isothermal (NpT) Monte Carlo simulation at the second-order Moller-Plesset perturbation theory level (MP2) has been performed. The obtained value of the water density is excellent (1.02 g/mL), and the calculated radial distribution functions are in fair agreement with experimental data. The MP2 results are compared to a few density functional approximations, including semilocal functionals, hybrid functionals, and functionals including empirical dispersion corrections. These results demonstrate the feasibility of directly sampling the potential energy surface of condensed-phase systems using correlated wave function theory, and their quality paves the way for further applications. Understanding the structural and electronic properties of liquid water at ambient conditions is a major challenge in condensed matter simulations. Water is a crucial ingredient for a large variety of systems of prime importance in basic chemistry, biology, and physics, as well as in the applied fields of catalysis and energy production. The water molecule has a large dipole moment and polarizability, is a multiple hydrogen donor and acceptor and can easily build network structures.The total cohesive energy in the condensed phase is, as a consequence of these properties, a sum of many weak interactions. Theoretical models face therefore the challenge to describe many different effects and their subtle interplay at a high precision. The development of sophisticated empirical potentials for water 1-10 , allowed to gain insights into water's behavior and its thermodynamic properties [11][12][13] , such as, density maxima, heat capacity and effects of supercooling. However, empirical models lack transferability and might fail if used under conditions away from their fitting range. Most importantly, as soon as water takes an active role in a chemical process, either as a strongly interacting solvent, or for example as a source of protons, the electronic properties of the water molecule need to be taken into account. In this respect, first-principles methods offer the possibility to describe all the underlying physics on the same footing, simplifying the treatment of intra-and inter-molecular interactions. The capability to reproduce properties of complex systems such as liquid water can therefore be used to judge the sophistication and predictive power of a given quantum mechanical model. Density functional theory (DFT) is the most used quantum mechanical method employed for studying physical and chemical properties of condensed phase systems. Many DFT based simulation of bulk water have been reported in the literature, and in this context three main methods of sampling the phase space can be recognized 14 : the Car-Parrinello molecula...

The dielectric properties of the hydrogen disordered hexagonal phase (Ih) of water ice have been computed using density functional theory (DFT) based Monte Carlo simulations in the isobaric isothermal ensemble. Temperature dependent data yield a fit for the Curie-Weiss law of the system and hence a prediction of the temperature of the phase transition from the Ih phase to the hydrogen ordered ice XI phase. Direct simulations around the phase transition temperature confirm and refine the predicted phase transition temperatures and provide data for further properties, such as the linear thermal expansion coefficient. Results have been obtained with both hybrid and semilocal density functionals, which yields insight in the performance of the electronic structure method. In particular, the hybrid functional yields significantly more realistic dielectric constants than the semilocal variant, namely epsilon approximate to 116 as opposed to epsilon approximate to 151 at 273 K (epsilon(experiment) = 95). This can be attributed to the tendency of semilocal functionals to be biased to configurations with a large dipole moment, and their overestimation of the dipole moments of these configurations. This is also reflected in the estimates of the Ih/XI transition temperature, which is 70-80 and 90-100 K for the hybrid and semilocal functional respectively. DFT based sampling of the millions of configurations necessary for this work has been enabled by a Tree Monte Carlo algorithm, designed for massively parallel computers. with both hybrid and semi-local density functionals, which yields insight in the performance of the electronic structure method. In particular, the hybrid functional yields significantly more realistic dielectric constants than the semi-local variant, namely ε ≈ 116 as opposed to ε ≈ 151 at 273K (ε experiment = 95). This can be attributed to the tendency of semi-local functionals to be biased to configurations with a large dipole moment, and their overestimation of the dipole moments of these configurations. This is also reflected in the estimates of the Ih/XI transition temperature, which is 70-80K and 90-100K for the hybrid and semi-local functional respectively.DFT based sampling of the millions of configurations necessary for this work has been enabled by a Tree Monte Carlo algorithm, designed for massively parallel computers.

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Der vorliegende Übersichtsartikel berichtet über Fortschritte in der molekularen Modellierung und Simulation mittels massiv‐paralleler Hoch‐ und Höchstleistungsrechner (HPC). Im SkaSim‐Projekt arbeiteten dazu Partner aus der HPC‐Community mit Anwendern aus Wissenschaft und Industrie zusammen. Ziel dabei war es mittels HPC‐Methoden die Vorhersage von thermodynamischen Stoffdaten in Bezug auf Effizienz, Qualität und Zuverlässigkeit weiter zu optimieren. In diesem Zusammenhang wurden verschiedene Themen bearbeitet: Atomistische Simulation der homogenen Gasblasenbildung, Oberflächenspannung klassischer Fluide und ionischer Flüssigkeiten, multikriterielle Optimierung molekularer Modelle, Weiterentwicklung der Simulationscodes ls1 mardyn und ms2, atomistische Simulation von Gastrennprozessen, molekulare Membran‐Strukturgeneratoren, Transportwiderstände und gemischtypenspezifische Bewertung prädiktiver Stoffdatenmodelle.