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Compositional disorder is common in crystal compounds. In these compounds, some atoms are randomly distributed at some crystallographic sites. For such compounds, randomness forms many non-identical independent structures. Thus, calculating…

Materials Science · Physics 2022-12-23 Mostafa Yaghoobi , Mojtaba Alaei

Quantitative prediction of electronic properties in correlated materials requires simulations without empirical truncations and parameters. We present a method to achieve this goal through a new ab initio formulation of dynamical mean-field…

Strongly Correlated Electrons · Physics 2021-04-08 Tianyu Zhu , Garnet Kin-Lic Chan

Electronic-structure theory is a strong pillar of materials science. Many different computer codes that employ different approaches are used by the community to solve various scientific problems. Still, the precision of different packages…

Accurate first-principles calculations for the energies, charge distributions, and spin symmetries of many-electron systems are essential to understand and predict the electronic and structural properties of molecules and materials.…

Chemical Physics · Physics 2024-01-24 Yuming Shi , Yi Shi , Adam Wasserman

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) codes are commonly treated as a "black box" in high-throughput screening of materials, with users opting for the default values of the input parameters. Often, non-experts may not sufficiently consider the…

Materials Science · Physics 2021-09-08 Jeremy J. Jorgensen , Gus L. W. Hart

We present a machine-learned (ML) model of kinetic energy for orbital-free density functional theory (OF-DFT) suitable for bulk light weight metals and compounds made of group III-V elements. The functional is machine-learned with Gaussian…

Materials Science · Physics 2025-02-11 Johann Lüder , Manabu Ihara , Sergei Manzhos

One may predict a quasicrystal structure starting from electrons and quantum mechanics, as approximated by interatomic pair potentials calibrated with ab-initio total-energy calculations, combined with the experimentally known composition…

Condensed Matter · Physics 2007-05-23 Christopher L. Henley , Marek Mihalkovic , Michael Widom

This work continues a program to systematically generalize the Skyrme Hartree-Fock method for medium and heavy nuclei by applying effective field theory (EFT) methods to Kohn-Sham density functional theory (DFT). When conventional Kohn-Sham…

Nuclear Theory · Physics 2007-05-23 Anirban Bhattacharyya , R. J. Furnstahl

This research work introduces the DFT through FP-LAPW+lo technique in WIEN2k software to obtain information about structural, thermoelectric, and optoelectronic characteristics of CaZnC and CaZnSi materials. The structural optimization was…

Materials Science · Physics 2025-12-29 P. K. Kamlesh , U. K. Gupta , S. Verma , M. Rani , Y. Toual , A. S. Verma

Performing density functional theory (DFT) calculations requires a careful choice of computational parameters to ensure convergence and obtain meaningful results. This represents a particularly important problem for high-throughput and…

Density Functional Theory (DFT) is one of the most widely used methods for "ab initio" calculations of the structure of atoms, molecules, crystals, surfaces, and their interactions. Unfortunately, the customary introduction to DFT is often…

Physics Education · Physics 2010-12-07 Nathan Argaman , Guy Makov

We present a $\Delta$-machine learning model for obtaining Kohn-Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine learned force field (MLFF) scheme based on the kernel method to…

Chemical Physics · Physics 2023-10-11 Shashikant Kumar , Xin Jing , John E. Pask , Andrew J. Medford , Phanish Suryanarayana

We compare two different approaches to investigations of many-electron systems. The first is the Hartree-Fock (HF) method and the second is the Density Functional Theory (DFT). Overview of the main features and peculiar properties of the HF…

Materials Science · Physics 2009-11-07 M. Ya. Amusia , A. Z. Msezane , V. R. Shaginyan

Molecules can form myriad crystalline polymorphs, each with distinct properties affecting their performance across diverse applications, from pharmaceuticals to functional materials and more. Predicting the thermodynamically most stable…

First-principles simulations of electronic properties of hybrid inorganic/organic interfaces are challenging, as common density-functional theory (DFT) approximations target specific material classes like bulk semiconductors or gas-phase…

Materials Science · Physics 2023-02-13 Jannis Krumland , Caterina Cocchi

Perdew et al. [Phys. Rev. Lett 49, 1691 (1982)] discovered and proved two different properties of exact Kohn-Sham density functional theory (DFT): (i) The exact total energy versus particle number is a series of linear segments between…

Other Condensed Matter · Physics 2015-03-13 Tamar Stein , Jochen Autschbach , Niranjan Govind , Leeor Kronik , Roi Baer

We have carried out a large scale computational investigation to assess the utility of common small-molecule force fields for computational screening of low energy conformers of typical organic molecules. Using statistical analyses on the…

Chemical Physics · Physics 2017-08-15 Ilana Y. Kanal , John A. Keith , Geoffrey R. Hutchison

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…

We describe a simple method to determine, from ab initio calculations, the complete orientation-dependence of interfacial free energies in solid-state crystalline systems. We illustrate the method with an application to precipitates in the…