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Density-functional theory (DFT) has been widely used to study water and ice for at least 20 years. However, the reliability of different DFT exchange-correlation (xc) functionals for water remains a matter of considerable debate. This is…

The derivative discontinuity in the exact exchange-correlation potential of ensemble Density Functional Theory (DFT) is investigated at the specific integer number that corresponds to the maximum number of bound electrons, $J_{max}$. A…

Quantum Physics · Physics 2011-11-09 Daniel L. Whitenack , Yu Zhang , Adam Wasserman

Machine learning (ML) has recently gained attention as a means to develop more accurate exchange-correlation (XC) functionals for density functional theory, but functionals developed thus far need to be improved on several metrics,…

Chemical Physics · Physics 2022-03-14 Kyle Bystrom , Boris Kozinsky

The density matrix renormalization group (DMRG) method has already proved itself as a very efficient and accurate computational method, which can treat large active spaces and capture the major part of strong correlation. Its application on…

Chemical Physics · Physics 2022-10-31 Pavel Beran , Katarzyna Pernal , Fabijan Pavosevic , Libor Veis

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.…

In approximate density functional theory (DFT), the self-interaction error is an electron delocalization anomaly associated with underestimated insulating gaps. It exhibits a predominantly quadratic energy-density curve that is amenable to…

Chemical Physics · Physics 2016-12-21 Glenn Moynihan , Gilberto Teobaldi , David D. O'Regan

The demand for pseudopotentials constructed for a given exchange-correlation (XC) functional far exceeds the supply, necessitating the use of those commonly available. The number of XC functionals currently available is in the hundreds, if…

Materials Science · Physics 2024-11-01 Marcin Maździarz

Motivated by the resurgence of electronic and optical property design in ordered fluoride and oxyfluoride compounds, we present a density functional theory (DFT) study on 19 materials with structures, ranging from simple to complex, and…

Materials Science · Physics 2016-11-23 Nenian Charles , James M. Rondinelli

The widespread use of (generalized) Kohn-Sham density functional theory (KS-DFT) lies in the fact that hierarchical sets of approximations of the exchange-correlation (XC) energy functional can be designed, offering versatile choices to…

Materials Science · Physics 2023-01-31 Igor Ying Zhang , Xinguo Ren

Increasing interest in sustainable synthesis of ammonia, nitrates, and urea has led to an increase in studies of catalytic conversion between nitrogen-containing compounds using heterogeneous catalysts. Density functional theory (DFT) is…

Materials Science · Physics 2024-06-21 Honghui Kim , Neung-Kyung Yu , Nianhan Tian , Andrew J. Medford

A new density functional theory (DFT) exchange-correlation functional for the exploration of reaction mechanisms is proposed. This new functional, denoted BMK (Boese-Martin for Kinetics), has an accuracy in the 2 kcal/mol range for…

Chemical Physics · Physics 2007-05-23 A. Daniel Boese , Jan M. L. Martin

Though deep neural networks have achieved impressive success on various vision tasks, obvious performance degradation still exists when models are tested in out-of-distribution scenarios. In addressing this limitation, we ponder that the…

Computer Vision and Pattern Recognition · Computer Science 2023-01-18 Xiaotong Li , Zixuan Hu , Jun Liu , Yixiao Ge , Yongxing Dai , Ling-Yu Duan

One of the most promising techniques used for studying the electronic properties of materials is based on Density Functional Theory (DFT) approach and its extensions. DFT has been widely applied in traditional solid state physics problems…

Materials Science · Physics 2013-06-03 Nicola Varini , Davide Ceresoli , Layla Martin-Samos , Ivan Girotto , Carlo Cavazzoni

Density functional theory is the standard theory for computing the electronic structure of materials, which is based on a functional that maps the electron density to the energy. However, a rigorous form of the functional is not known and…

Materials Science · Physics 2021-12-02 Ryo Nagai , Ryosuke Akashi , Osamu Sugino

The journey of theoretical study on semiconductors is reviewed in a non-conventional way. We have started with the basic introduction of Hartree-Fock method and introduce the fundamentals of Density Functional Theory (DFT). From the oldest…

Materials Science · Physics 2021-05-04 Sujoy Datta , Debnarayan Jana

Standard flavors of density-functional theory (DFT) calculations are known to fail in describing anions, due to large self-interaction errors. The problem may be circumvented by using localized basis sets of reduced size, leaving no…

Chemical Physics · Physics 2019-12-23 Francesco Nattino , Céline Dupont , Nicola Marzari , Oliviero Andreussi

In this work, we extend the source-free (SF) exchange correlation (XC) functional developed by Sangeeta Sharma and co-workers to plane-wave density functional theory (DFT) based on the projector augmented wave (PAW) method. This constraint…

Materials Science · Physics 2024-05-28 Guy C. Moore , Matthew K. Horton , Aaron D. Kaplan , Sinéad M. Griffin , Kristin A. Persson

Rare-earth oxides (REOs) are an important class of materials owing to their unique properties, including high ionic conductivities, large dielectric constants, and elevated melting temperatures, making them relevant to several technological…

We present an accurate local density-functional for electronic-structure calculations within the density functional theory (DFT). The functional is derived by analyzing the structure of the standard perturbative expansion of the correlation…

Materials Science · Physics 2024-11-28 Mario Benites , Angel Rosado , Efstratios Manousakis

Double-machine-learning pipelines for the Average Dose-Response Function rely on kernel-weighted local-linear smoothers, which inherit unbounded functional influence: a single outlier within a kernel window biases the curve across the…

Machine Learning · Statistics 2026-05-04 Eichi Uehara
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