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To explore the potential of molecular gas treatment of freshly cut lithium foils in non-electrolyte based passivation of high energy-density Li anodes, density functional theory (DFT) has been used to study the decomposition of molecular…
The success of density functional theory for the description of the adsorption of atoms on surfaces is well established, and based on recent calculations using gradient corrections, it has been shown that it also describes well the…
A detailed exploration of the $f$-atomic orbital occupancy space for UO$_2$ is performed using a first principles approach based on density functional theory (DFT), employing a full hybrid functional within a systematic basis set.…
The contribution to the free energy for a film of liquid of thickness $h$ on a solid surface, due to the interactions between the solid-liquid and liquid-gas interfaces is given by the binding potential, $g(h)$. The precise form of $g(h)$…
Machine learning interatomic potentials (MLIPs) have revolutionized computational materials science by bridging the gap between quantum mechanical accuracy and classical simulation efficiency, enabling unprecedented exploration of materials…
The stationary functional of the all-electron density functional plus dynamical mean field theory (DFT+DMFT) formalism to perform free energy calculations and structural relaxations is implemented for the first time. Here, the first order…
We examine the out-of-equilibrium dynamical evolution of density profiles of ultrasoft particles under time-varying external confining potentials in three spatial dimensions. The theoretical formalism employed is the dynamical density…
Classical density functional theory (cDFT) and dynamical density functional theory (DDFT) are modern statistical mechanical theories for modeling many-body colloidal systems at the one-body density level. The theories hinge on knowing the…
This work assesses a classical density functional theory (DFT) model for predicting macroscopic static contact angles of pure substances and mixtures by comparison to own experimental data. We employ a DFT with a Helmholtz energy functional…
Machine learning (ML) models utilizing structure-based features provide an efficient means for accurate property predictions across diverse chemical spaces. However, obtaining equilibrium crystal structures typically requires expensive…
Density functional theory (DFT) is an efficient instrument for describing a wide range of nanoscale phenomena: wetting transition, capillary condensation, adsorption, etc. In this paper, we suggest a method for obtaining the equilibrium…
Machine learning (ML) of kinetic energy functionals (KEF) for orbital-free density functional theory (OF-DFT) holds the promise of addressing an important bottleneck in large-scale ab initio materials modeling where sufficiently accurate…
In contrast to the original Kohn-Sham (KS) formalism, we propose a density functional theory (DFT) with fractional orbital occupations for the study of ground states of many-electron systems, wherein strong static correlation is shown to be…
Large scale first-principles calculations based on density functional theory (DFT) employing two different methods (atomic orbitals and plane wave basis sets) were used to study the energetics, geometry, the electronic charge redistribution…
Various methods going beyond density-functional theory (DFT), such as DFT+U, hybrid functionals, meta-GGAs, GW, and DFT-embedded dynamical mean field theory (eDMFT), have been developed to describe the electronic structure of correlated…
In this study we employ Density Functional Theory (DFT) methods to investigate the surface energy barrier for electron emission (surface barrier) and thermodynamic stability of Ba and Ba-O species adsorption under conditions of high…
We describe a test particle approach based on dynamical density functional theory (DDFT) for studying the correlated time evolution of the particles that constitute a fluid. Our theory provides a means of calculating the van Hove…
We provide novel random surface density functional theory (RSDFT) formulation in the case of geometric heterogeneous surface of solid media which is essential for description of thermodynamic properties of confined fluids. The major…
Prediction of the electronic structure of functional materials is essential for the engineering of new devices. Conventional electronic structure prediction methods based on density functional theory (DFT) suffer from not only high…
The development of novel functional materials in experimental labs combined with computer-based compound simulation brings the vision of materials design on a microscopic scale continuously closer to reality. For many applications interface…