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Multi-center transition metal complexes (MCTMs) with magnetically interacting ions have been proposed as components for information processing devices and storage units. For any practical application of MCTMs as magnetic units, it is…

Chemical Physics · Physics 2023-04-03 Henry C. Fitzhugh , James W. Furness , Mark R. Pederson , Juan E. Peralta , Jianwei Sun

In recent years, a number of dynamical density functional theories (DDFTs) have been developed for describing the dynamics of the one-body density of both colloidal and atomic fluids. In the colloidal case, the particles are assumed to have…

Soft Condensed Matter · Physics 2009-08-10 A. J. Archer

Static electric response properties of atoms and molecules are reported within the real-space Cartesian grid implementation of pseudopotential Kohn-Sham (KS) density functional theory (DFT). A detailed systematic investigation is made for a…

Chemical Physics · Physics 2019-04-26 Tanmay Mandal , Abhisek Ghosal , Amlan K. Roy

Sparse matter is characterized by regions with low electron density and its understanding calls for methods to accurately calculate both the van der Waals (vdW) interactions and other bonding. Here we present a first-principles density…

Materials Science · Physics 2010-06-15 Elisa Londero , Elsebeth Schroder

Nonintegrable systems thermalize, leading to the emergence of fluctuating hydrodynamics. Typically, this hydrodynamics is diffusive. We use the effective field theory (EFT) of diffusion to compute higher-point functions of conserved…

Strongly Correlated Electrons · Physics 2024-02-14 Luca V. Delacretaz , Ruchira Mishra

Density-functional theory (DFT) has been widely used to study water and ice for at least 20 years. However, the reliability of different DFT exchange-correlation (xc) functionals for water remains a matter of considerable debate. This is…

We show how machine learning techniques based on Bayesian inference can be used to reach new levels of realism in the computer simulation of molecular materials, focusing here on water. We train our machine-learning algorithm using…

Materials Science · Physics 2013-02-25 Albert P. Bartok , Michael J. Gillan , Frederick R. Manby , Gabor Csanyi

We consider a system of particles interacting via a purely repulsive, soft-core potential recently introduced to model effective pair interactions between dendrimers, which is expected to lead to the formation of crystals with multiple…

Soft Condensed Matter · Physics 2015-05-11 Davide Pini

Standard density functional approximations often give questionable results for odd-electron radical complexes, with the error typically attributed to self-interaction. In density corrected density functional theory (DC-DFT), certain classes…

Chemical Physics · Physics 2015-06-19 Min-Cheol Kim , Eunji Sim , Kieron Burke

Predicting interfacial thermodynamics across molecular and continuum scales remains a central challenge in computational science. Classical density functional theory (cDFT) provides a first-principles route to connect microscopic…

Computational Physics · Physics 2026-01-01 Edoardo Monti , Peter Yatsyshin , Konstantinos Gkagkas , Andrew B. Duncan

We present a plane-wave basis set implementation of charge constrained density functional molecular dynamics (CDFT-MD) for simulation of electron transfer reactions in condensed phase systems. Following earlier work of Wu et al. Phys. Rev.…

Chemical Physics · Physics 2015-05-13 H. Oberhofer , J. Blumberger

The dynamical and thermodynamic phase stabilities of the stoichiometric compound CrN including different structural and magnetic configurations are comprehensively investigated using a first-principles density-functional-theory (DFT) plus U…

Machine learning has emerged as a powerful tool for predicting molecular properties in chemical reaction networks with reduced computational cost. However, accurately predicting energies of transition state (TS) structures remains a…

Chemical Physics · Physics 2025-04-29 Stefan Gugler , Markus Reiher

This article reviews a method for calculating an equilibrium interfacial phase diagram depicting regions of stability for different interface structures as function of temperature and chemical potentials. Density functional theory (DFT) is…

Materials Science · Physics 2016-11-23 Sven A. E. Johansson , G. Wahnström

The influence of a chemically or electrically heterogeneous distribution of interaction sites at a planar substrate on the number density of an adjacent fluid is studied by means of classical density functional theory (DFT). In the case of…

Soft Condensed Matter · Physics 2018-05-25 Maximilian Mußotter , Markus Bier , S. Dietrich

Electron transfer with changing occupation in the 4f subshell poses a considerable challenge for quantitative predictions in quantum chemistry. Using the example of cerium oxide, we identify the main deficiencies of common…

Chemical Physics · Physics 2021-12-07 Tobias Schäfer , Nathan Daelman , Núria López

Hydrodynamic density functional theory (DFT) is applied to analyse dynamic contact angles of droplets in order to assess its predictive capability regarding wetting phenomena at the microscopic scale and to evaluate its feasibility for…

Fluid Dynamics · Physics 2025-08-06 Benjamin Bursik , Rolf Stierle , Hamza Oukili , Martin Schneider , Gernot Bauer , Joachim Gross

We present an accurate local density-functional for electronic-structure calculations within the density functional theory (DFT). The functional is derived by analyzing the structure of the standard perturbative expansion of the correlation…

Materials Science · Physics 2024-11-28 Mario Benites , Angel Rosado , Efstratios Manousakis

Fluids with competing short range attraction and long range repulsive interactions between the particles can exhibit a variety of microphase separated structures. We develop a lattice-gas (generalised Ising) model and analyse the phase…

Soft Condensed Matter · Physics 2016-01-20 Blesson Chacko , Christopher Chalmers , Andrew J. Archer

Accelerated discovery with machine learning (ML) has begun to provide the advances in efficiency needed to overcome the combinatorial challenge of computational materials design. Nevertheless, ML-accelerated discovery both inherits the…

Materials Science · Physics 2022-05-09 Chenru Duan , Fang Liu , Aditya Nandy , Heather J. Kulik
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