Adopting an accurate kinetic energy density functional (KEDF) to characterize the noninteracting kinetic energy within the framework of orbital-free density functional theory (OFDFT) is challenging. We propose a new form of the non-local KEDF with a real-space truncation cutoff that satisfies the uniform electron gas limit and design KEDFs for simple metals and silicon. The new KEDFs are obtained by minimizing a residual function, which contains the differences in the total energy and charge density of several representative systems with respect to the Kohn-Sham DFT results. By systematically testing different cutoffs of the new KEDFs, we find that the cutoff plays a crucial role in determining the properties of metallic Al and semiconducto...
We present a kinetic-energy density-functional theory and the corresponding kinetic-energy Kohn-Sham...
Current research challenges in areas such as energy and bioscience have created a strong need for De...
Machine learning (ML) is an increasingly popular statistical tool for analyzing either measured or c...
Orbital-free density functional theory (OF-DFT) constitutes a computationally highly effective tool ...
Density functional (DF) theory has proved to be a powerful way to determine the ground state energy ...
We assess several generalized gradient approximations (GGAs) and Laplacian-level meta-GGAs (LL-MGGA)...
The development of novel Kinetic Energy (KE) functionals is an important topic in density functional...
This thesis focuses on the use and development of electronic structure methods in the density functi...
In Kohn-Sham (KS) density functional theory, the kinetic energy (KE) functional is described by fic...
Within ``orbital-free'' density functional theory, it is essential to develop general kinetic energy...
Abstract In the beginning of quantum mechanical Density-Functional Theory (DFT), there was the Thoma...
Kinetic energy (KE) approximations are key elements in orbital-free density functional theory. To da...
The use of energy functionals based on charge density as the basic variable is advocated for ab init...
Bu tezde silisyum, germanyum ve ikili yarıiletken bileşiklerin taban durumunda örgü sabiti, bant a...
Frozen density embedding (FDE) theory is one of the major techniques aiming to bring modeling of ext...
We present a kinetic-energy density-functional theory and the corresponding kinetic-energy Kohn-Sham...
Current research challenges in areas such as energy and bioscience have created a strong need for De...
Machine learning (ML) is an increasingly popular statistical tool for analyzing either measured or c...
Orbital-free density functional theory (OF-DFT) constitutes a computationally highly effective tool ...
Density functional (DF) theory has proved to be a powerful way to determine the ground state energy ...
We assess several generalized gradient approximations (GGAs) and Laplacian-level meta-GGAs (LL-MGGA)...
The development of novel Kinetic Energy (KE) functionals is an important topic in density functional...
This thesis focuses on the use and development of electronic structure methods in the density functi...
In Kohn-Sham (KS) density functional theory, the kinetic energy (KE) functional is described by fic...
Within ``orbital-free'' density functional theory, it is essential to develop general kinetic energy...
Abstract In the beginning of quantum mechanical Density-Functional Theory (DFT), there was the Thoma...
Kinetic energy (KE) approximations are key elements in orbital-free density functional theory. To da...
The use of energy functionals based on charge density as the basic variable is advocated for ab init...
Bu tezde silisyum, germanyum ve ikili yarıiletken bileşiklerin taban durumunda örgü sabiti, bant a...
Frozen density embedding (FDE) theory is one of the major techniques aiming to bring modeling of ext...
We present a kinetic-energy density-functional theory and the corresponding kinetic-energy Kohn-Sham...
Current research challenges in areas such as energy and bioscience have created a strong need for De...
Machine learning (ML) is an increasingly popular statistical tool for analyzing either measured or c...