Related papers: Understanding the Density Maximum of Water with Ma…
Ab initio molecular dynamics simulations of liquid water under equilibrium ambient conditions, together with a novel energy decomposition analysis, have recently shown that a substantial fraction of water molecules exhibit a significant…
Introduction of polarizability in classical molecular simulations holds the promise to increase accuracy as well as prediction power to computer modeling. To introduce polarizability in a straight-forward way one strategy is based on Drude…
Water keeps puzzling scientists because of its numerous properties which behave oppositely to usual liquids: for instance, water expands upon cooling, and liquid water is denser than ice. To explain this anomalous behaviour, several…
We perform an extensive computational study of binary mixtures of water and short-chain alcohols resorting to two-scale potential models to account for the singularities of hydrogen bonded liquids. Water molecules are represented by a well…
Simulating water from first principles remains a significant computational challenge due to the slow dynamics of the underlying system. Although machine-learned interatomic potentials (MLPs) can accelerate these simulations, they often fail…
Using molecular dynamics simulations and integral equations (Rogers-Young, Percus-Yevick and hypernetted chain closures) we investigate the thermodynamic of particles interacting with continuous core-softened intermolecular potential.…
The anomalous behavior of liquid water is widely associated with a liquid-liquid phase transition between high- and low-density states in the supercooled regime. At the microscopic level, tetrahedral hydrogen-bond networks govern these…
Methanol-water liquid mixtures have been investigated by high-energy synchrotron X-ray and neutron diffraction at low temperatures. We are thus able to report the first complete sets of both X-ray and neutron weighted total scattering…
We introduce machine learning (ML) models that predict the electronic structure of materials across a wide temperature range. Our models employ neural networks and are trained on density functional theory (DFT) data. Unlike most other ML…
We introduce a local machine-learning method for predicting the electron densities of periodic systems. The framework is based on a numerical, atom-centred auxiliary basis, which enables an accurate expansion of the all-electron density in…
The isothermal compressibility of water is essential to understand its anomalous properties. We compute it by ab initio molecular dynamics simulations of 200 molecules at five densities, using two different van der Waals density…
The isothermal compressibility (i.e., the asymptotic number variance) of equilibrium liquid water as a function of temperature is minimal near ambient conditions. This anomalous non-monotonic temperature dependence is due to a balance…
We use molecular dynamics simulations in two dimensions to investigate the possibility that a core-softened potential can reproduce static and dynamic anomalies found experimentally in liquid water: (i) the increase in specific volume upon…
{It has recently been proposed that giant molecular complexes form at the sites where streams of diffuse warm atomic gas collide at transonic velocities.} {We study the global statistics of molecular clouds formed by large scale colliding…
We present results and discuss methods for computing the melting temperature of dense molecular hydrogen using a machine learned model trained on quantum Monte Carlo data. In this newly trained model, we emphasize the importance of accurate…
Liquid polymorphism is an intriguing phenomenon which has been found in a few single-component systems, the most famous being water. By supercooling liquid Te to more than 130 K below its melting point and performing simultaneous…
The growth of homogeneously nucleated droplets in water vapor at the fixed temperatures T=273, 283, 293, 303, 313, 323, 333, 343, 353, 363 and 373 K (the pressure $p=1$ atm.) is investigated on the basis of the coarse-grained molecular…
Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex aqueous systems such as solid-liquid interfaces. Here, we present a machine learning…
While the interactions between water molecules are dominated by strongly directional hydrogen bonds (HBs), it was recently proposed that relatively weak, isotropic van der Waals (vdW) forces are essential for understanding the properties of…
While the water molecule is simple, its condensed phase liquid behavior is so complex that no consensus description has emerged despite three centuries of effort. Here we identify features of its behavior that are the most peculiar, hence…