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Electrons in zero external magnetic field can be studied with density functional theory (DFT) or with spin-DFT (SDFT). The latter is normally used for open shell systems because its approximations appear to model better the exchange and…

Chemical Physics · Physics 2022-04-06 Timothy Callow , Benjamin Pearce , Nikitas Gidopoulos

In the past decade, classical dynamical density functional theory (DDFT) has been developed and widely applied to the Brownian dynamics of interacting colloidal particles. One of the possible derivation routes of DDFT from the microscopic…

Soft Condensed Matter · Physics 2014-01-28 Raphael Wittkowski , Hartmut Löwen , Helmut R. Brand

Over many years, computational simulations based on Density Functional Theory (DFT) have been used extensively to study many different materials at the atomic scale. However, its application is restricted by system size, leaving a number of…

Mesoscale and Nanoscale Physics · Physics 2018-12-05 Carlos Romero-Muñiz , Ayako Nakata , Pablo Pou , David R. Bowler , Tsuyoshi Miyazaki , Rubén Pérez

Classical density functional theory (cDFT) provides a systematic approach to predict the structure and thermodynamic properties of chemical systems through the single-molecule density profiles. Whereas the statistical-mechanical framework…

Chemical Physics · Physics 2024-11-07 Jinni Yang , Runtong Pan , Jikai Sun , Jianzhong Wu

Electronic friction-Langevin dynamics (EF-LD) provides an efficient framework for capturing nonadiabatic effects at solid surfaces, with particular relevance to electrochemistry and molecular electronics. In this work, we investigate…

Chemical Physics · Physics 2026-05-26 Yunhao Liu , Wenjie Dou

The properties of electrons in matter are of fundamental importance. They give rise to virtually all molecular and material properties and determine the physics at play in objects ranging from semiconductor devices to the interior of giant…

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…

Quantum-mechanical simulations can offer atomic-level insights into chemical processes on surfaces. This understanding is crucial for the rational design of new solid catalysts as well as materials to store energy and mitigate greenhouse…

Classical dynamical density functional theory (DDFT) is one of the cornerstones of modern statistical mechanics. It is an extension of the highly successful method of classical density functional theory (DFT) to nonequilibrium systems.…

Soft Condensed Matter · Physics 2020-12-29 Michael te Vrugt , Hartmut Löwen , Raphael Wittkowski

We present a computational approach for electronically correlated metallic surfaces and interfaces, which combines Density Functional and Dynamical Mean Field Theory using a multi-orbital perturbative solver for the many-body problem. Our…

Strongly Correlated Electrons · Physics 2022-04-06 Andrea Droghetti , Miloš M. Radonjić , Anita Halder , Ivan Rungger , Liviu Chioncel

We give a detailed description of a recently proposed first principles approach to the electronic structure of strongly correlated materials. The method combines the GW approximation with dynamical mean field theory. It is designed to…

Strongly Correlated Electrons · Physics 2007-05-23 Ferdi Aryasetiawan , Silke Biermann , Antoine Georges

Density Functional Theory (DFT) is a pivotal method within quantum chemistry and materials science, with its core involving the construction and solution of the Kohn-Sham Hamiltonian. Despite its importance, the application of DFT is…

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

Dynamical mean-field theory (DMFT) is a cornerstone technique for studying strongly correlated electronic systems. However, each DMFT step is computationally demanding, and many iterations can be required to achieve convergence. Here, we…

Strongly Correlated Electrons · Physics 2026-01-26 E. M. Makaresz , O. Gingras , Tsung-Han Lee , Nicola Lanatà , B. J. Powell , Henry L. Nourse

Multicomponent density functional theory (DFT) enables the consistent quantum mechanical treatment of both electrons and protons. A major challenge has been the design of electron-proton correlation functionals that produce even…

Chemical Physics · Physics 2017-09-26 Yang Yang , Kurt R. Brorsen , Tanner Culpitt , Michael V. Pak , Sharon Hammes-Schiffer

The convergence to the self-consistency in the dynamical-mean-field-theory (DMFT) calculations for models of correlated electron systems can be significantly accelerated by using an appropriate mixing of hybridization functions which are…

Strongly Correlated Electrons · Physics 2009-11-11 Rok Zitko

We have investigated the electron correlation effect on the electronic structures and transport properties of the iron-based superconductors using the density functional theory (DFT) and dynamical mean field theory (DMFT). By considering…

Strongly Correlated Electrons · Physics 2011-08-19 Hyo Seok Ji , Geunsik Lee , Ji Hoon Shim

We develop a classical density functional theory (DFT) for two site associating fluids in spatially uniform external fields which exhibit orientational inhomogeneities. The Helmholtz free energy functional is obtain using Wertheim's…

Soft Condensed Matter · Physics 2015-06-17 B. D. Marshall , W. G. Chapman , M. M. Telo da Gama

Density functional theory (DFT) is routinely employed in material science and in quantum chemistry to simulate weakly correlated electronic systems. Recently, deep learning (DL) techniques have been adopted to develop promising functionals…

Strongly Correlated Electrons · Physics 2023-10-02 Emanuele Costa , Rosario Fazio , Sebastiano Pilati

While density functional theory (DFT) serves as a prevalent computational approach in electronic structure calculations, its computational demands and scalability limitations persist. Recently, leveraging neural networks to parameterize the…

Computational Physics · Physics 2024-06-18 Yang Zhong , Hongyu Yu , Jihui Yang , Xingyu Guo , Hongjun Xiang , Xingao Gong
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