相关论文: A first-principles machine-learning force field fo…
Molecular simulations employing empiric force fields have provided valuable knowledge about the ice growth process in the last decade. The development of novel computational techniques allows us to study this process, which requires long…
Classical empirical force fields have dominated biomolecular simulation for over 50 years. Although widely used in drug discovery, crystal structure prediction, and biomolecular dynamics, they generally lack the accuracy and transferability…
We examine ice crystal growth from water vapor at temperatures near the melting point, when surface premelting creates a quasiliquid layer at the solid/vapor interface. Recent ice growth measurements as a function of vapor supersaturation…
We investigate the structural similarities between liquid water and 53 ices, including 20 knowncrystalline phases. We base such similarity comparison on the local environments that consist of atoms within a certain cutoff radius of a…
Icephobic surfaces inspired by superhydrophobic surfaces offer a passive solution to the problem of icing. However, modeling icephobicity is challenging because some material features that aid superhydrophobicity can adversely affect the…
The results of experiments on the formation of molecular hydrogen on low density and high density amorphous ice surfaces are analyzed using a rate equation model. The activation energy barriers for the relevant diffusion and desorption…
Triangular lattice models for pattern formation by hard-core soft-shell particles at interfaces are introduced and studied in order to determine the effect of the shell thickness and structure. In model I, we consider particles with…
Machine learning offers an unprecedented perspective for the problem of classifying phases in condensed matter physics. We employ neural-network machine learning techniques to distinguish finite-temperature phases of the strongly correlated…
We perform a systematic application of the hybrid particle-field molecular dynamics technique [Milano et al, J. Chem. Phys. 2009, 130, 214106] to study interfacial properties and potential of mean force (PMF) for separating nanoparticles…
Ice nucleation is a process of great relevance in physics, chemistry, technology and environmental sciences, much theoretical and experimental efforts have been devoted to its understanding, but still it remains a topic of intense research.…
Using statistical field theory supplemented with molecular dynamics simulations, we consider premelting on the surface of ice as a generic consequence of broken hydrogen bonds at the boundary between the condensed and gaseous phases. A…
Atomistic simulations provide insights into structure-property relations on an atomic size and length scale, that are complementary to the macroscopic observables that can be obtained from experiments. Quantitative predictions, however, are…
We derive the energy of the surface between the normal and superfluid components of a mixed phase of a system composed of two particle species with different densities. The surface energy is obtained by the integration of the free energy…
The microstructure of snow determines its fundamental properties such as the mechanical strength, reflectivity, or the thermo-hydraulic properties. Snow undergoes continuous microstructural changes due to local gradients in temperature,…
Abridged. It is important for the star formation process to understand the collapse of a prestellar dense core. We investigate the effect of the magnetic field during the first collapse up to the formation of the firstcore, focusing…
In studying solidification process by simulations on the atomic scale, the modeling of crystal nucleation or amorphisation requires the construction of interatomic interactions that are able to reproduce the properties of both the solid and…
In recent years, machine learning has emerged as a powerful computational tool and novel problem-solving perspective for physics, offering new avenues for studying strongly interacting QCD matter properties under extreme conditions. This…
Context. Interstellar surface chemistry is a complex process that occurs in icy layers accumulated onto grains of different sizes. Efficiency of surface processes often depends on the immediate environment of adsorbed molecules. Aims. We…
X-ray diffraction is ideal for probing sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and…
Machine learning force fields (MLFFs) have emerged as a sophisticated tool for cost-efficient atomistic simulations approaching DFT accuracy, with recent message passing MLFFs able to cover the entire periodic table. We present an invariant…