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In this manuscript, we present a general computational method for characterizing the molecular structure of liquid water interfaces as sampled from atomistic simulations. With this method, the interfacial structure is quantified based on…
Axion-like particles (ALPs) that decay into photon pairs pose a challenge for experiments that rely on the construction of a decay vertex in order to search for long-lived particles. This is particularly true for beam-dump experiments,…
Hydration properties of graphene oxide (GO) are essential for most of its potential applications. In this work, we employ atomistic molecular dynamics simulations to investigate seven GO compositions with different levels of oxygenation.…
Machine-learned potential-driven molecular dynamics (MLMD) simulations are of great value in guiding the design and optimization of memory devices. Amorphous indium-tin-oxide (ITO) is widely used as transparent conducting oxide for…
We investigate the morphologies of the Ge(001) surface that are produced by bombardment with a normally incident, broad argon ion beam at sample temperatures above the recrystallization temperature. Two previously-observed kinds of…
Graphene oxide (GO) holds significant promise for electronic devices and nanocomposite materials. A number of models were proposed for GO structure, combining carboxyl, hydroxyl, carbonyl and epoxide groups at different locations. The…
Metal nanoparticle surfaces comprise of multiple planes with various atomic arrangements that interact with gases differently1,2. Identification of gas adsorption properties on all facets is an essential prerequisite for rational design of…
The photo-induced desorption and oxidation of CO on Ru(0001) is simulated using ab initio molecular dynamics with electronic friction that accounts for the non-equilibrated excited electrons and phonons. Different (O,CO) coverages are…
Adsorption of carbon monoxide (CO) on transition-metal surfaces is a prototypical process in surface sciences and catalysis. Despite its simplicity, it has posed great challenges to theoretical modeling. Pretty much all existing density…
Materials databases built from calculations based on density functional approximations play an important role in the discovery of materials with improved properties. Most databases thus constructed rely on the generalized gradient…
Here we present the application of an advanced Sparse Gaussian Process based machine learning algorithm to the challenge of predicting the yields of inertial confinement fusion (ICF) experiments. The algorithm is used to investigate the…
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 accuracy of classical physical property predictions using molecular dynamics simulations is determined by the quality of the interatomic potentials. Here we introduce a training approach for empirical interatomic potentials (EIPs) which…
The electronic structure of single crystals Na$_{0.6}$CoO$_2$, which are closely related to the superconducting Na$_{0.3}$CoO$_2$.$y$H$_2$O ($T_c \sim 5K$), is studied by angle-resolved photoelectron spectroscopy. While the measured Fermi…
The honeycomb lattice iridate Na$_2$IrO$_3$ shows frustrated magnetism and can potentially display Kitaev-like exchange interactions. Recently, it was shown that the electronic properties of the surface of crystalline Na$_2$IrO$_3$ can be…
Matter density is formally infinite at the location of caustic surfaces, where dark matter sheet folds in phase-space. The caustics separate regions with different number of streams and the volume elements change the parity by turning…
Likely candidates for the global potential energy minima of (H$_{2}$O)$_{n}$ clusters with $n\leq21$ on the (0001)-surface of graphite are found using basin-hopping global optimization. The potential energy surfaces are constructed using…
Machine learning interatomic potentials have revolutionized complex materials design by enabling rapid exploration of material configurational spaces via crystal structure prediction with ab initio accuracy. However, critical challenges…
Atomic structures and adatom geometries of surfaces encode information about the thermodynamics and kinetics of the processes that lead to their formation, and which can be captured by a generative physical model. Here we develop a workflow…
We present and discuss the results of calculations of surface relaxations and rumplings for the (001) and (011) surfaces of BaTiO3 and PbTiO3, using a hybrid B3PW description of exchange and correlation. On the (001) surfaces, we consider…