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Density functional theory (DFT) is a cornerstone of computational chemistry and materials science, but its computational cost limits its use in large-scale and high-throughput applications. While machine learning has accelerated energy…

Chemical Physics · Physics 2026-03-18 Yingdi Jin , Xinming Qin , Ruichen Liu , Jie Liu , Zhenyu Li , Jinlong Yang

With the rapid advancement of machine learning techniques for materials simulations, machine-learned force fields (MLFFs) have become a powerful tool that complements first-principles calculations by enabling high-accuracy molecular…

Materials Science · Physics 2026-01-16 Zicun Li , Huanjing Gong , Ruijuan Xiao , Xinguo Ren

A formulation of the density functional theory is constructed on the foundations of entropic inference. The theory is introduced as an application of maximum entropy for inhomogeneous fluids in thermal equilibrium. It is shown that entropic…

Statistical Mechanics · Physics 2023-12-29 Ahmad Yousefi , Ariel Caticha

Noncollinear (NC) magnetism and spin-orbit coupling (SOC) are indispensable for predictive ab initio materials simulations with pronounced relativistic effects and magnetic frustration, yet they significantly increase the cost of…

Orbital-free density functional theory (OF-DFT) is a promising method for large-scale quantum mechanics simulation as it provides a good balance of accuracy and computational cost. Its applicability to large-scale simulations has been aided…

Density functional theory (DFT) has been a cornerstone in computational chemistry, physics, and materials science for decades, benefiting from advancements in computational power and theoretical methods. This paper introduces a novel,…

We propose an in-silico experiment to introduce classical density functional theory (cDFT). Den- sity functional theories, whether quantum or classical, rely on abstract concepts that are non- intuitive. However, they are at the heart of…

Chemical Physics · Physics 2014-10-16 Guillaume Jeanmairet , Nicolas Levy , Maximilien Levesque , Daniel Borgis

Combination of deep learning and ab initio calculation has shown great promise in revolutionizing future scientific research, but how to design neural network models incorporating a priori knowledge and symmetry requirements is a key…

Computational Physics · Physics 2023-06-12 Xiaoxun Gong , He Li , Nianlong Zou , Runzhang Xu , Wenhui Duan , Yong Xu

Effective field theory (EFT) methods are applied to density functional theory (DFT) as part of a program to systematically go beyond mean-field approaches to medium and heavy nuclei. A system of fermions with short-range, natural…

Nuclear Theory · Physics 2007-05-23 S. J. Puglia , A. Bhattacharyya , R. J. Furnstahl

Embedded density functional theory (e-DFT) is used to describe the electronic structure of strongly interacting molecular subsystems. We present a general implementation of the Exact Embedding (EE) method [J. Chem. Phys. 133, 084103 (2010)]…

Other Condensed Matter · Physics 2011-07-27 Jason D. Goodpaster , Taylor A. Barnes , Thomas F. Miller

We analyze the methodology and the performance of subsystem density functional theory (DFT) with meta-generalized gradient approximation (meta-GGA) exchange-correlation functionals for non-bonded systems. Meta-GGA functionals depend on the…

Other Condensed Matter · Physics 2015-05-05 S. Śmiga , E. Fabiano , S. Laricchia , L. A. Constantin , F. Della Sala

Exchange hole is the principle constituent in density functional theory, which can be used to accurately design exchange energy functional and range separated hybrid functionals coupled with some appropriate correlation. Recently, density…

Materials Science · Physics 2017-09-14 Bikash Patra , Subrata Jana , Prasanjit Samal

By partitioning the electron density into subsystem contributions, the Frozen Density Embedding (FDE) formulation of subsystem DFT has recently emerged as a powerful tool for reducing the computational scaling of Kohn--Sham DFT. To date,…

Materials Science · Physics 2015-06-22 Alessandro Genova , Davide Ceresoli , Michele Pavanello

Metal-organic frameworks (MOFs) are nanoporous compounds composed of metal ions and organic linkers. MOFs play an important role in industrial applications such as gas separation, gas purification, and electrolytic catalysis. Important MOF…

Machine Learning · Computer Science 2020-11-02 Shehtab Zaman , Christopher Owen , Kenneth Chiu , Michael Lawler

With an increasing number of new scientific papers being released, it becomes harder for researchers to be aware of recent articles in their field of study. Accurately classifying papers is a first step in the direction of personalized…

Other Condensed Matter · Physics 2023-03-21 Marie Dumaz , Camila Romero-Bohorquez , Donald Adjeroh , Aldo H. Romero

In the last 50 years, equilibrium density functional theory (DFT) has been proven to be a powerful, versatile and predictive approach for the statics and structure of classical particles. This theory can be extended to the nonequilibrium…

Soft Condensed Matter · Physics 2021-02-26 Hartmut Löwen

Density functional theory (DFT) became a universal approach to compute ground-state and excited configurations of many-electron systems held together by an external one-body potential in condensed-matter, atomic, and molecular physics. At…

Nuclear Theory · Physics 2011-09-30 J. Dobaczewski

We present the theory and implementation of a fully variational wave function -- density functional theory (DFT) hybrid model, which is applicable to many cases of strong correlation. We denote this model the multiconfigurational…

Density functional theory (DFT) is a fundamental method for simulating quantum chemical properties, but it remains expensive due to the iterative self-consistent field (SCF) process required to solve the Kohn-Sham equations. Recently, deep…

Computational Physics · Physics 2025-10-23 Seongsu Kim , Nayoung Kim , Dongwoo Kim , Sungsoo Ahn

Two (so-called left and right) variants of N-centered ensemble density-functional theory (DFT) [Senjean and Fromager, Phys. Rev. A 98, 022513 (2018)] are presented. Unlike the original formulation of the theory, these variants allow for the…

Strongly Correlated Electrons · Physics 2020-02-25 Bruno Senjean , Emmanuel Fromager
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