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Density-functional theory is a formally exact description of a many-body quantum system in terms of its density; in practice, however, approximations to the universal density functional are required. In this work, a model based on deep…

Computational Physics · Physics 2016-08-02 Jeffrey M. McMahon

Although the classical density functional theory (DFT) of inhomogeneous fluids was formulated more than four decades ago, its application to broken symmetry phases of molecular systems remained a challenge. Approximate free energy…

Statistical Mechanics · Physics 2026-05-19 Yashwant Singh

Practical density functional theory (DFT) owes its success to the groundbreaking work of Kohn and Sham that introduced the exact calculation of the non-interacting kinetic energy of the electrons using an auxiliary mean-field system.…

Chemical Physics · Physics 2023-11-17 P. del Mazo-Sevillano , J. Hermann

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…

Energy functionals serve as the basis for different models and methods in quantum and classical many-particle physics. Arguably, one of the most successful and widely used approaches in material science at both ambient and extreme…

Plasma Physics · Physics 2024-10-22 Z. Moldabekov , J. Vorberger , T. Dornheim

Parametric correlations are studied in several classes of covariant density functional theories (CDFTs) using a statistical analysis in a large parameter hyperspace. In the present manuscript, we investigate such correlations for two…

Nuclear Theory · Physics 2020-03-17 A. Taninah , S. E. Agbemava , A. V. Afanasjev , P. Ring

Computational chemistry is a powerful tool for the discovery of novel materials. In particular, it is used to simulate ionic liquids in search of electrolytes for electrochemical applications. Herein, the choice of the computational method…

Atomic and Molecular Clusters · Physics 2024-05-16 Karl Karu , Maksin Mišin , Heigo Ers , Jianwei Sun , Vladisav Ivaništšev

Improving the accuracy and thus broadening the applicability of electronic density functional theory (DFT) is crucial to many research areas, from material science, to theoretical chemistry, biophysics and biochemistry. In the last three…

Strongly Correlated Electrons · Physics 2019-03-27 Paola Gori-Giorgi , Michael Seidl

Density functional theory is the standard theory for computing the electronic structure of materials, which is based on a functional that maps the electron density to the energy. However, a rigorous form of the functional is not known and…

Materials Science · Physics 2021-12-02 Ryo Nagai , Ryosuke Akashi , Osamu Sugino

The standard model of classical Density Functional Theory for pair potentials consists of a hard-sphere functional plus a mean-field term accounting for long ranged attraction. However, most implementations using sophisticated Fundamental…

Computational Physics · Physics 2021-01-04 James F. Lutsko , Cédric Schoonen

The enormous structural and chemical diversity of metal-organic frameworks (MOFs) forces researchers to actively use simulation techniques on an equal footing with experiments. MOFs are widely known for outstanding adsorption properties, so…

Materials Science · Physics 2021-11-22 Vadim V. Korolev , Yurii M. Nevolin , Thomas A. Manz , Pavel V. Protsenko

Linear-scaling implementations of density functional theory (DFT) reach their intended efficiency regime only when applied to systems having a physical size larger than the range of their Kohn-Sham density matrix (DM). This causes a problem…

Chemical Physics · Physics 2022-03-25 Marcel David Fabian , Ben Shpiro , Eran Rabani , Daniel Neuhauser , Roi Baer

Atomistic modeling is a widely employed theoretical method of computational materials science. It has found particular utility in the study of magnetic materials. Initially, magnetic empirical interatomic potentials or spin-polarized…

Atomic Physics · Physics 2024-07-02 Tatiana S. Kostiuchenko , Alexander V. Shapeev , Ivan S. Novikov

We outline the general framework of machine learning (ML) methods for multi-scale dynamical modeling of condensed matter systems, and in particular of strongly correlated electron models. Complex spatial temporal behaviors in these systems…

Strongly Correlated Electrons · Physics 2022-01-06 Puhan Zhang , Sheng Zhang , Gia-Wei Chern

Density functional theory (DFT) offers a desirable balance between quantitative accuracy and computational efficiency in practical many-electron calculations. Its central component, the exchange-correlation energy functional, has been…

Molecular-level understanding of the interactions between the constituents of an atomic structure is essential for designing novel materials in various applications. This need goes beyond the basic knowledge of the number and types of…

Development of the electronic kinetic-energy density functional is a subject of major interest in theoretical physics and chemistry. In this work, the nonlocal kinetic-energy functional is developed in terms of the response function for the…

Chemical Physics · Physics 2022-06-17 Hideaki Takahashi

First principles methods can provide insight into materials that is otherwise impossible to acquire. Density Functional Theory (DFT) has been the first principles method of choice for numerous applications, but it falls short of predicting…

Materials Science · Physics 2019-07-24 Arpita Paul , Turan Birol

The electrostatic interaction between two non-identical, moderately charged colloids situated in close proximity of each other at a fluid interface is studied. By resorting to a well-justified model system, this problem is analytically…

Soft Condensed Matter · Physics 2018-04-30 Arghya Majee , Timo Schmetzer , Markus Bier

Computational virtual high-throughput screening (VHTS) with density functional theory (DFT) and machine-learning (ML)-acceleration is essential in rapid materials discovery. By necessity, efficient DFT-based workflows are carried out with a…

Materials Science · Physics 2021-06-25 Chenru Duan , Shuxin Chen , Michael G. Taylor , Fang Liu , Heather J. Kulik