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In the last few years several ``universal'' interatomic potentials have appeared, using machine-learning approaches to predict energy and forces of atomic configurations with arbitrary composition and structure, with an accuracy often…
State-of-the-art methods for calculating neutral excitation energies are typically demanding and limited to single electron-hole pairs and their composite plasmons. Here we introduce excitonic density-functional theory (XDFT) a…
Molecules can form myriad crystalline polymorphs, each with distinct properties affecting their performance across diverse applications, from pharmaceuticals to functional materials and more. Predicting the thermodynamically most stable…
We explore the consequences of imposing robust thermodynamic constraints arising from perturbative Quantum Chromodynamics (QCD) when inferring the dense-matter equation-of-state (EOS). We find that the termination density, up to which the…
This study analyzes and contrasts different phenomenological methods used to model the nuclear equation of state (EOS) for neutron star matter based on covariant energy density functionals (CEDF). Using two complementary methodologies, we…
Quantum embedding schemes have the potential to significantly reduce the computational cost of first principles calculations, whilst maintaining accuracy, particularly for calculations of electronic excitations in complex systems. In this…
The atomic and electronic structures of Pd3N, PdN and PdN2 were investigated using ab initio density-functional theory (DFT). We studied cohesive energy vs. volume equation of states (EOS) for a set of reported and hypothetical structures.…
A general set of methods is presented for calculating chemical potentials in solid and liquid mixtures using {\em ab initio} techniques based on density functional theory (DFT). The methods are designed to give an {\em ab initio} approach…
Quantum-chemical processes in liquid environments impact broad areas of science, from molecular biology to geology to electrochemistry. While density-functional theory (DFT) has enabled efficient quantum-mechanical calculations which…
We present an updated general purpose nuclear equation of state (EoS) for use in simulations of core-collapse supernovae, neutron star mergers and black hole collapse. This EoS is formulated in the context of Density Functional Theory (DFT)…
Machine Learning (ML) approximations to Density Functional Theory (DFT) potential energy surfaces (PESs) are showing great promise for reducing the computational cost of accurate molecular simulations, but at present they are not applicable…
We introduce Effective Atom Theory (EAT), a framework that transforms combinatorial materials design into a smooth, gradient-driven optimization within density functional theory (DFT). Atoms are represented as probabilistic mixtures of…
In the present work, the atomic and the electronic structures of Au3N, AuN and AuN2 are investigated using first-principles density-functional theory (DFT). We studied cohesive energy vs. volume data for a wide range of possible structures…
Choosing optimal representation methods of atomic and electronic structures is essential when machine learning properties of materials. We address the problem of representing quantum states of electrons in a solid for the purpose of machine…
New energy-density functionals (EDFs) inspired by effective-field theories (EFTs) have been recently proposed. The present work focuses on three of such functionals which were developed to produce satisfactory equations of state for nuclear…
We have developed a method that can analyze large random grain boundary (GB) models with the accuracy of density functional theory (DFT) calculations using active learning. It is assumed that the atomic energy is represented by the linear…
The self consistent version of the density functional theory (DFT) is presented, which allows to calculate the ground state and dynamic properties of finite multi-electron systems such as atoms, molecules and clusters. The exact functional…
We propose a means for constructing highly accurate equations of state (EOS) for elemental solids and liquids essentially from first principles, based upon a particular decomposition of the underlying condensed matter Hamiltonian for the…
Calculating perturbation response properties of materials from first principles provides a vital link between theory and experiment, but is bottlenecked by the high computational cost. Here a general framework is proposed to perform density…
Due to its favorable computational efficiency time-dependent (TD) density functional theory (DFT) enables the prediction of electronic spectra in a high-throughput manner across chemical space. Its predictions, however, can be quite…