相关论文: Machine Learning Potentials for Hydrogen Absorptio…

A comprehensive phase diagram of lowest-energy structures and compositions of the rutile TiO_2(110) surface in equilibrium with a surrounding gas phase at finite temperatures and pressures has been determined using density functional theory…

We study the physical properties of a homogeneous sample of 157 optically-thick absorption line systems at redshifts ~1.8-4.4, selected from a high-dispersion spectroscopic survey of Lyman limit systems (LLSs). By means of multiple…

For a long time, there have been huge discrepancies between different models and experiments concerning the liquid-liquid phase transition (LLPT) in dense hydrogen. In this work, we present the results of extensive calculations of the LLPT…

Due the alarming rate of climate change, the implementation of efficient CO$_2$ capture has become crucial. This project aims to create an algorithm that predicts the uptake of CO$_2$ adsorbing Metal-Organic Frameworks (MOFs) by using…

Biphasic interfaces are complex but fascinating regimes that display a number of properties distinct from those of the bulk. The CO$_2$-H$_2$O interface, in particular, has been the subject of a number of studies on account of its…

Machine learning potentials (MLPs) represent atomic interactions with quantum mechanical accuracy offering an efficient tool for atomistic simulations in many fields of science. However, most MLPs rely on local atomic energies without…

The theoretical exploration of the phase diagrams of binary hydrides under pressure using \emph{ab initio} crystal structure prediction techniques coupled with first-principles calculations has led to the \emph{in silico} discovery of…

We construct a fast, transferable, general purpose, machine-learning interatomic potential suitable for large-scale simulations of $N_2$. The potential is trained only on high quality quantum chemical molecule-molecule interactions, no…

First principles molecular dynamics simulations reveal a liquid-liquid phase transition in supercooled elemental silicon. Two phases coexist below $T_c\approx 1232K$. The low density phase is nearly tetra-coordinated, with a pseudogap at…

We present a study of the galaxy environment of 9 strong HI+CIV absorption line systems ($16.2<{\rm log}(N({\rm HI}))<21.2$) spanning a wide range in metallicity at $z\sim4-5$, using MUSE integral field and X-Shooter spectroscopic data…

Machine learning interatomic potentials (MLIPs) enable large-scale atomistic simulations but remain challenged in describing mixed-valence materials where charge ordering strongly influences thermodynamic stability. Here we investigate the…

The study of the formation of molecular hydrogen on low temperature surfaces is of interest both because it allows to explore elementary steps in the heterogeneous catalysis of a simple molecule and because of the applications in…

Liquid-liquid and liquid-vapor coexistence regions of various water models were determined by MC simulations of isotherms of density fluctuation restricted systems and by Gibbs ensemble MC simulations. All studied water models show multiple…

High-entropy alloys (HEAs) have attracted increasing attention due to their unique structural and functional properties. In the study of HEAs, thermodynamic properties and phase stability play a crucial role, making phase diagram…

We present the first large, blind and uniformly selected survey for molecular hydrogen (H_2) in damped Lyman alpha systems (DLAs) with moderate-to-high resolution spectra. 86 DLAs were searched for absorption in the many Lyman and Werner…

For many machine learning applications in science, data acquisition, not training, is the bottleneck even when avoiding experiments and relying on computation and simulation. Correspondingly, and in order to reduce cost and carbon…

Absorption spectra of liquid water at 300 K are calculated from both classical and density functional theory molecular dynamics simulation data, which together span from 1 MHz to hundreds of THz, agreeing well with experimental data…

Unraveling the atomistic and the electronic structure of solid-liquid interfaces is the key to the design of new materials for many important applications, from heterogeneous catalysis to battery technology. Density functional theory (DFT)…

Physisorption of hydrogen molecules in metal-organic frameworks (MOFs) provides a promising way for hydrogen storage, in which the van der Waals (vdW) interaction plays an important role but cannot described by the density functional theory…

We investigate the transferability of machine learning interatomic potentials across concentration variations in chemically similar systems, using aqueous potassium hydroxide solutions as a case study. Despite containing identical chemical…