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We generalise the non-affine theory of viscoelasticity for use with large, well-sampled systems of arbitrary chemical complexity. Having in mind predictions of mechanical and vibrational properties of amorphous systems with atomistic…

Disordered Systems and Neural Networks · Physics 2020-07-27 Ivan Kriuchevskyi , Vladimir V. Palyulin , Rico Milkus , Robert M. Elder , Timothy W. Sirk , Alessio Zaccone

We present a method for total energy minimizations and molecular dynamics simulations based either on tight-binding or on Kohn-Sham hamiltonians. The method leads to an algorithm whose computational cost scales linearly with the system…

Condensed Matter · Physics 2009-10-22 Francesco Mauri , Giulia Galli

Machine learning is employed to build an energy density functional for self-bound nuclear systems for the first time. By learning the kinetic energy as a functional of the nucleon density alone, a robust and accurate orbital-free density…

Nuclear Theory · Physics 2022-03-21 X. H. Wu , Z. X. Ren , P. W. Zhao

We introduce a practical hybrid approach that combines orbital-free density functional theory (DFT) with Kohn-Sham DFT for speeding up first-principles molecular dynamics simulations. Equilibrated ionic configurations are generated using…

We develop a method in which the electronic densities of small fragments determined by Kohn-Sham density functional theory (DFT) are embedded using stochastic DFT to form the exact density of the full system. The new method preserves the…

Chemical Physics · Physics 2015-06-19 Daniel Neuhauser , Roi Baer , Eran Rabani

We present an efficient preconditioning technique for accelerating the fixed point iteration in real-space Kohn-Sham density functional theory (DFT) calculations. The preconditioner uses a low rank approximation of the dielectric matrix…

Materials Science · Physics 2023-03-29 Sambit Das , Vikram Gavini

Orbital-free (OF) methods promise significant speed-up of computations based on density functional theory (DFT). In this field, the development of accurate kinetic-energy density functionals remains an open question. In this chapter we…

Materials Science · Physics 2013-05-03 Constantine Yannouleas , Uzi Landman

Using the Wentzel-Kramers-Brillouin method, we derive a modified form of the Thomas-Fermi approximation to electron density. This new result enables us to calculate the details of the self-consistent ion cores, as well as the ionization…

Materials Science · Physics 2009-02-23 Gregory C. Dente , Michael L. Tilton

In the exact Kohn-Sham density-functional theory (DFT), the total energy versus the number of electrons is a series of linear segments between integer points. However, commonly used approximate density functionals produce total energies…

Materials Science · Physics 2013-04-03 Eli Kraisler , Leeor Kronik

We suggest to include the density of electron charge explicitly in the electron potential of density functional theory, rather than implicitly via exchange-correlation functionals. The advantages of the approach are conceptual and…

Materials Science · Physics 2007-05-23 Werner A. Hofer , Krisztian Palotas

An interesting fundamental problem in density-functional theory of electronic structure of matter is to construct the exact Kohn-Sham (KS) potential for a given density. The exact potential can then be used to assess the accuracy of…

Atomic and Molecular Clusters · Physics 2019-05-22 Ashish Kumar , Rabeet Singh , Manoj K. Harbola

Modeling high temperature (10's or 100's of eV), dense plasmas is challenging due to the multitude of non-negligible physical effects including significant partial ionization and multi-site effects. These effects cause the breakdown or…

Computational Physics · Physics 2018-05-16 C. E. Starrett

In this paper, we introduce a highly accurate and efficient numerical solver for the radial Kohn--Sham equation. The equation is discretized using a high-order finite element method, with its performance further improved by incorporating a…

Numerical Analysis · Mathematics 2024-11-08 Zheming Luo , Yang Kuang

The Ziman formulation of electrical conductivity is tested in warm and hot dense matter using the pseudo-atom molecular dynamics method. Several implementation options that have been widely used in the literature are systematically tested…

Plasma Physics · Physics 2015-09-15 D. J. Burrill , D. Feinblum , M. R. J. Charest , C. E. Starrett

KSSOLV (Kohn-Sham Solver) is a MATLAB toolbox for performing Kohn-Sham density functional theory (DFT) calculations with a plane-wave basis set. KSSOLV 2.0 preserves the design features of the original KSSOLV software to allow users and…

This paper derives and demonstrates a new, purely density-based ab initio approach for calculation of the energies and properties of many-electron systems. It is based upon the discovery of relationships that govern the "mechanics" of the…

Chemical Physics · Physics 2024-09-04 James C. Ellenbogen

This article addresses a fundamental problem faced by the ab initio community: the lack of an effective formalism for the rapid exploration and exchange of new methods. To rectify this, we introduce a novel, basis-set independent,…

Materials Science · Physics 2009-10-31 Sohrab Ismail-Beigi , T. A. Arias

Nonlocal kinetic energy density functionals (KEDFs) with density-dependent kernels are currently the most accurate functionals available for orbital-free density functional theory (OF-DFT) calculations. However, despite advances in…

Materials Science · Physics 2024-12-05 Yongshuo Chen , Cheng Ma , Boning Cui , Tian Cui , Wenhui Mi , Qiang Xu , Yanchao Wang , Yanming Ma

Density functional theory is the workhorse of modern electronic structure calculations, with wide-ranging applications in chemistry, physics, materials science, and machine learning. At its heart lies the exchange-correlation functional, a…

Chemical Physics · Physics 2026-02-20 Fabien Tran , Susi Lehtola , Stefano Pittalis , Miguel A. L. Marques

The recently developed Deep Potential [Phys. Rev. Lett. 120, 143001, 2018] is a powerful method to represent general inter-atomic potentials using deep neural networks. The success of Deep Potential rests on the proper treatment of locality…

Computational Physics · Physics 2019-12-05 Leonardo Zepeda-Núñez , Yixiao Chen , Jiefu Zhang , Weile Jia , Linfeng Zhang , Lin Lin
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