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Functional oxide perovskites are the pillar of cutting-edge technological applications. Density functional theory (DFT) simulations are the theoretical methods of choice to understand and design perovskite materials. However, tests on the…

Materials Science · Physics 2020-05-11 Kiel T. Williams , Lucas K. Wagner , Claudio Cazorla , Tim Gould

The present contribution does not aim at replacing the huge and often excellent literature on DFT for atomic nuclei, but tries to provide an updated introduction to this topic. The goal would be, ideally, to help a fresh M.Sc. or Ph.D.…

Nuclear Theory · Physics 2019-08-09 G. Colò

Nuclear density functional theory (DFT) is the only microscopic, global approach to the structure of atomic nuclei. It is used in numerous applications, from determining the limits of stability to gaining a deep understanding of the…

Nuclear Theory · Physics 2015-02-06 Nicolas Schunck , Jordan D. McDonnell , Jason Sarich , Stefan M. Wild , Dave Higdon

The knowledge of effective masses is a key ingredient to analyze numerous properties of semiconductors, like carrier mobilities, (magneto-)transport properties, or band extrema characteristics yielding carrier densities and density of…

The formally exact framework of equilibrium Density Functional Theory (DFT) is capable of simultaneously and consistently describing thermodynamic and structural properties of interacting many-body systems in arbitrary external potentials.…

We present DFT-FE 1.0, building on DFT-FE 0.6 [Comput. Phys. Commun. 246, 106853 (2020)], to conduct fast and accurate large-scale density functional theory (DFT) calculations (reaching ~ $100,000$ electrons) on both many-core CPU and…

Computational Physics · Physics 2022-08-31 Sambit Das , Phani Motamarri , Vishal Subramanian , David M. Rogers , Vikram Gavini

We validate the application of our recent orbital-free density functional theory (DFT) approach, [Phys. Rev. Lett. 113, 155006 (2014)], for the calculation of ionic and electronic transport properties of dense plasmas. To this end, we…

Plasma Physics · Physics 2015-12-16 Travis Sjostrom , Jérôme Daligault

Starting from Newton's equations of motion, we derive a dynamical density functional theory (DDFT) applicable to atomic liquids. The theory has the feature that it requires as input the Helmholtz free energy functional from equilibrium…

Soft Condensed Matter · Physics 2007-05-23 A. J. Archer

The combination of density functional theory with dynamical mean-field theory (DFT+DMFT) has become a powerful first-principles approach to tackle strongly correlated materials in condensed matter physics. The wide use of this approach…

Strongly Correlated Electrons · Physics 2022-05-10 Xin Qu , Peng Xu , Rusong Li , Gang Li , Lixin He , Xinguo Ren

Density Functional Theory (DFT) is the de facto workhorse for large-scale electronic structure calculations in chemistry and materials science. While plane-wave DFT implementations remain the most widely used, real-space DFT provides…

We present a numerical method for grand canonical density functional theory (DFT) tailored to solid-state systems, employing Gaussian-type orbitals as the primary basis. Our approach directly minimizes the grand canonical free energy using…

Chemical Physics · Physics 2025-10-09 Anton Z. Ni , Adam Rettig , Joonho Lee

Density Functional Tight-Binding (DFTB), an approximative approach derived from Density Functional Theory (DFT), has the potential to pave the way for simulations of large periodic or non-periodic systems. We have specifically tailored DFTB…

Realistic prediction of the superconducting transition temperature (Tc) for PdH is a long-standing challenge, because it depends on robust calculations of the electron and phonon band structures to obtain the electron-phonon scattering…

Materials Science · Physics 2022-08-08 Samaneh Sadat Setayandeh , Tim Gould , Toktam Morshedloo , Evan Gray

The marriage of density functional theory (DFT) and deep learning methods has the potential to revolutionize modern computational materials science. Here we develop a deep neural network approach to represent DFT Hamiltonian (DeepH) of…

Materials Science · Physics 2023-01-02 He Li , Zun Wang , Nianlong Zou , Meng Ye , Runzhang Xu , Xiaoxun Gong , Wenhui Duan , Yong Xu

The structural, dynamical, and thermodynamical properties of diamond, graphite and layered derivatives (graphene, rhombohedral graphite) are computed using a combination of density-functional theory (DFT) total-energy calculations and…

Materials Science · Physics 2009-11-10 Nicolas Mounet , Nicola Marzari

In order to obtain a reasonably accurate and easily implemented approach to many-electron calculations, we will develop a new Density Functional Theory (DFT). Specifically, we derive an approximation to electron density, the first term of…

Materials Science · Physics 2010-04-23 Gregory C. Dente

Time-dependent density-functional theory (TDDFT) is widely used to describe electronic excitations in complex finite systems with large numbers of atoms, such as biomolecules and nanocrystals. The first part of this paper will give a simple…

Materials Science · Physics 2008-08-15 C. A. Ullrich , V. Turkowski

We compare the behavior of the finite-temperature Hartree-Fock model with that of thermal density functional theory using both ground-state and temperature-dependent approximate exchange functionals. The test system is bcc Li in the…

Materials Science · Physics 2013-11-26 Valentin V. Karasiev , Travis Sjostrom , S. B. Trickey

We introduce the unification of dynamical mean field theory (DMFT) and linear-scaling density functional theory (DFT), as recently implemented in ONETEP, a linear-scaling DFT package, and TOSCAM, a DMFT toolbox. This code can account for…

Strongly Correlated Electrons · Physics 2020-05-04 Edward B. Linscott , Daniel J. Cole , Nicholas D. M. Hine , Michael C. Payne , Cédric Weber

Atomistic simulations provide insights into structure-property relations on an atomic size and length scale, that are complementary to the macroscopic observables that can be obtained from experiments. Quantitative predictions, however, are…

Materials Science · Physics 2021-04-14 Nataliya Lopanitsyna , Chiheb Ben Mahmoud , Michele Ceriotti