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We present a numerical modeling workflow based on machine learning (ML) which reproduces the the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible…

Density functional theory (DFT) is a powerful theoretical tool widely used in such diverse fields as computational condensed matter physics, atomic physics, and quantum chemistry. DFT establishes that a system of $N$ interacting electrons…

Plasma Physics · Physics 2020-04-29 Giovanni Manfredi

Kohn-Sham density functional theory is the base of modern computational approaches to electronic structures. Their accuracy vitally relies on the exchange-correlation energy functional, which encapsulates electron-electron interaction…

Computational Physics · Physics 2019-11-04 Ryo Nagai , Ryosuke Akashi , Osamu Sugino

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

The systematic underestimation of band gaps is one of the most fundamental challenges in semilocal density functional theory (DFT). In addition to hindering the application of DFT to predicting electronic properties, the band gap problem is…

Chemical Physics · Physics 2024-08-27 Kyle Bystrom , Stefano Falletta , Boris Kozinsky

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

We present a reformulation of QM/MM as a fully quantum mechanical theory of interacting subsystems, all treated at the level of density functional theory (DFT). For the MM subsystem, which lacks orbitals, we assign an ad hoc electron…

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…

We combine techniques from quantum and from classical density functional theory (DFT) to describe electron-ion mixtures. For homogeneous systems, we show how to calculate ion-ion and ion-electron correlation functions within Chihara's…

Materials Science · Physics 2007-05-23 A. A. Louis , H. Xu , J. A. Anta

Kohn-Sham density functional theory (DFT) is the standard method for first-principles calculations in computational chemistry and materials science. More accurate theories such as the random-phase approximation (RPA) are limited in…

Materials Science · Physics 2023-10-25 Stefan Riemelmoser , Carla Verdi , Merzuk Kaltak , Georg Kresse

Unlike covalent two-dimensional (2D) materials like graphene, 2D metals have non-layered structures due to their non-directional, metallic bonding. While experiments on 2D metals are still scarce and challenging, density-functional theory…

Materials Science · Physics 2023-01-06 Kameyab Raza Abidi , Pekka Koskinen

The Local Molecular Field Theory (LMF) developed by Weeks and co-workers has proved successful for treating the structure and thermodynamics of a variety of non-uniform liquids. By reformulating LMF in terms of one-body direct correlation…

Soft Condensed Matter · Physics 2015-06-12 A. J. Archer , R. Evans

Density functional theory (DFT), the most widely adopted method in modern computational chemistry, fails to describe accurately the electronic structure of strongly correlated systems. Here we show that DFT can be formally and practically…

Chemical Physics · Physics 2022-04-18 Daniel Gibney , Jan-Niklas Boyn , David A. Mazziotti

Kohn-Sham Density Functional Theory (KS-DFT) provides the exact ground state energy and electron density of a molecule, contingent on the as-yet-unknown universal exchange-correlation (XC) functional. Recent research has demonstrated that…

Density Functional Theory (DFT) stands as a widely used and efficient approach for addressing the many-electron Schr\"odinger equation across various domains such as physics, chemistry, and biology. However, a core challenge that persists…

Computational Engineering, Finance, and Science · Computer Science 2024-12-25 Sizhuo Jin , Shuo Chen , Jianjun Qian , Ying Tai , Jun Li

We study the accuracy of Kohn-Sham density functional theory (DFT) for warm- and hot-dense matter (WDM and HDM). Specifically, considering a wide range of systems, we perform accurate ab initio molecular dynamics simulations with…

Computational Physics · Physics 2024-11-21 Phanish Suryanarayana , Arpit Bhardwaj , Xin Jing , Shashikant Kumar , John E. Pask

Machine Learning (ML)-based force fields are attracting ever-increasing interest due to their capacity to span spatiotemporal scales of classical interatomic potentials at quantum-level accuracy. They can be trained based on high-fidelity…

Chemical Physics · Physics 2024-06-03 Sebastien Röcken , Julija Zavadlav

Density functional theory (DFT) is an essential building block for modern theoretical physics, chemistry, and engineering, especially those concerning electronic properties. Through decades of development, various program packages for…

Materials Science · Physics 2022-11-21 Yusuke Nomura , Ryosuke Akashi

Density functional theory (DFT) is one of the primary approaches to get a solution to the many-body Schrodinger equation. The essential part of the DFT theory is the exchange-correlation (XC) functional, which can not be obtained in…

Computational Physics · Physics 2021-12-10 Alexander Ryabov , Petr Zhilyaev

We train a neural network as the universal exchange-correlation functional of density-functional theory that simultaneously reproduces both the exact exchange-correlation energy and potential. This functional is extremely non-local, but…

Computational Physics · Physics 2019-10-10 Jonathan Schmidt , Carlos L. Benavides-Riveros , Miguel A. L. Marques