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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

Spectroscopic properties of molecules holds great importance for the description of the molecular response under the effect of an UV/Vis electromagnetic radiation. Computationally expensive ab initio (e.g. MultiConfigurational SCF, Coupled…

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

The practical success of density functional theory (DFT) is largely credited to the Kohn-Sham approach, which enables the exact calculation of the non-interacting electron kinetic energy via an auxiliary noninteracting system. Yet, the…

Computational Physics · Physics 2025-03-21 Sangita Majumdar , Zekun Shi , Giovanni Vignale

Orbital-free density functional theory promises to deliver linear-scaling electronic structure calculations. This requires the knowledge of the non-interacting kinetic-energy density functional (KEDF), which should be accurate and must…

Materials Science · Physics 2024-12-12 Michael A. J. Mitchell , Teresa Del Aguila Ferrandis , Stefano Sanvito

Koopmans-compliant functionals provide an orbital-density-dependent framework for an accurate evaluation of spectral properties; they are obtained by imposing a generalized piecewise-linearity condition on the total energy of the system…

Materials Science · Physics 2022-07-06 Riccardo De Gennaro , Nicola Colonna , Edward Linscott , Nicola Marzari

We showcase the advantages of orbital-free density-potential functional theory (DPFT), a more flexible variant of Hohenberg-Kohn density functional theory. DPFT resolves the usual trouble with the gradient-expanded kinetic energy functional…

Quantum Gases · Physics 2021-06-16 Martin-Isbjörn Trappe , Jun Hao Hue , Berthold-Georg Englert

In this work we get insight into the impact of reduced density matrix functionals on the quality of removal/addition energies obtained using the Extended Koopmans' Theorem (EKT). Within reduced density matrix functional theory (RDMFT) the…

Strongly Correlated Electrons · Physics 2022-12-26 S. Di Sabatino , J. Koskelo , J. A. Berger , P. Romaniello

Machine learning of kinetic energy functionals (KEF), in particular kinetic energy density (KED) functionals, has recently attracted attention as a promising way to construct KEFs for orbital-free density functional theory (OF-DFT). Neural…

Materials Science · Physics 2025-08-11 Sergei Manzhos , Johann Lüder , Manabu Ihara

Most realistic calculations of moderately correlated materials begin with a ground-state density functional theory (DFT) calculation. While Kohn-Sham DFT is used in about 40,000 scientific papers each year, the fundamental underpinnings are…

Strongly Correlated Electrons · Physics 2022-09-26 Kieron Burke , John Kozlowski

Density-potential functional theory (DPFT) is an alternative formulation of orbital-free density functional theory that may be suitable for modeling the electronic structure of large systems. To date, DPFT has been applied mainly to quantum…

Materials Science · Physics 2023-04-21 Martin-Isbjörn Trappe , William C. Witt , Sergei Manzhos

A combination of systematic density functional theory (DFT) calculations and machine learning techniques has a wide range of potential applications. This study presents an application of the combination of systematic DFT calculations and…

Materials Science · Physics 2015-06-17 Atsuto Seko , Tomoya Maekawa , Koji Tsuda , Isao Tanaka

Accurate computational predictions of metal-organic frameworks (MOFs) and their properties is crucial for discovering optimal compositions and applying them in relevant technological areas. This work benchmarks density functional theory…

Materials Science · Physics 2025-03-11 Joshua Edzards , Julia Santana Andreo , Holger-Dietrich Saßnick , Caterina Cocchi

Orbital-free Density Functional Theory (OF-DFT) has been used when studying atoms, molecules and solids. In nuclear physics, there has been basically no application of OF-DFT so far, as the Density Functional Theory (DFT) has been widely…

Nuclear Theory · Physics 2023-08-03 Gianluca Colo' , Kouichi Hagino

A way to improve the accuracy of the spectral properties in density functional theory (DFT) is to impose constraints on the effective, Kohn-Sham (KS), local potential [J. Chem. Phys. {\bf 136}, 224109 (2012)]. As illustrated, a convenient…

Chemical Physics · Physics 2023-05-22 Thomas C. Pitts , Sofia Bousiadi , Nikitas I. Gidopoulos , Nektarios N. Lathiotakis

Orbital-free density functional theory (OFDFT) offers a challenging way of electronic-structure calculations scaled as $\mathcal{O}(N)$ computation for system size $N$. We here develop a scheme of the OFDFT calculations based on the…

Computational Physics · Physics 2021-09-06 Fumihiro Imoto , Masatoshi Imada , Atsushi Oshiyama

We present an efficient computational approach to perform real-space electronic structure calculations using an adaptive higher-order finite-element discretization of Kohn-Sham density-functional theory (DFT). To this end, we develop an…

Computational Physics · Physics 2015-06-05 Phani Motamarri , Michael R Nowak , Kenneth Leiter , Jaroslaw Knap , Vikram Gavini

We have proposed a method for correcting the Kohn-Sham eigen energies in the density functional theory (DFT) based on the Koopmans theorem using Wannier functions. The method provides a general approach applicable for molecules and solids…

Computational Physics · Physics 2015-03-02 Jie Ma , Lin-Wang Wang

High throughput screening of materials for technologically relevant areas, like identification of better catalysts, electronic materials, ceramics for high temperature applications and drug discovery, is an emerging topic of research. To…

Chemical Physics · Physics 2020-05-04 Edgar Josué Landinez Borda , Amit Samanta

Range-separated hybrid functionals (RSH) with ``ionization energy'' and/or ``optimal tuning'' of the screening parameter have proven to be among the most practical and accurate approaches for describing excited-state properties across a…