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We develop new transfer learning algorithms to accelerate prediction of material properties from ab initio simulations based on density functional theory (DFT). Transfer learning has been successfully utilized for data-efficient modeling in…

Computational Physics · Physics 2020-07-01 Schuyler Krawczuk , Daniele Venturi

We present a first-principles methodology, within the context of linear-response theory, that greatly facilitates the perturbative study of physical properties of metallic crystals. Our approach builds on ensemble density-functional theory…

Materials Science · Physics 2024-01-31 Asier Zabalo , Massimiliano Stengel

The Kohn-Sham scheme of density functional theory is one of the most widely used methods to solve electronic structure problems for a vast variety of atomistic systems across different scientific fields. While the method is fast relative to…

Density functional approximations (DFAs) suffer from delocalization error, which limits their accuracy in predicting electron affinities (EAs), ionization potentials (IPs), and quasiparticle energies. In this work, we present a theoretical…

Chemical Physics · Physics 2026-04-07 Zipeng An , Xiaolong Yang , Xiao Zheng , Weitao Yang

A procedure for removing explicit orbital dependence from meta-generalized-gradient approximation (mGGA) exchange-correlation functionals by converting them into Laplacian-dependent functionals recently was developed by us and shown to be…

Materials Science · Physics 2018-10-03 Daniel Mejia-Rodriguez , S. B. Trickey

The incorporation of a strong interaction regime within the approximate, semilocal exchange-correlation functionals still remains a very challenging task for density functional theory. One of the promising attempts in this direction is the…

Other Condensed Matter · Physics 2023-09-20 Subrata Jana , Szymon Smiga , Lucian A. Constantin , Prasanjit Samal

Stimulated Raman Adiabatic Passage, a very efficient technique for manipulating a quantum system based on the adiabatic theorem, is analyzed in the case where the manipulated physical system is interacting with a spin bath. Exploitation of…

Quantum Physics · Physics 2023-11-21 Benedetto Militello , Anna Napoli

The construction of a better exchange-correlation potential in time-dependent density functional theory (TDDFT) can improve the accuracy of TDDFT calculations and provide more accurate predictions of the properties of many-electron systems.…

Quantum Physics · Physics 2023-08-23 Jun Yang , James D Whitfield

Adiabatic connection models (ACMs), which interpolate between the limits of weak and strong interaction, are powerful tools to build accurate exchange-correlation functionals. If the exact weak-interaction expansion from second-order…

Chemical Physics · Physics 2022-09-08 S. Śmiga , F. Della Sala , P. Gori-Giorgi , E. Fabiano

It is known that the adiabatic approximation in time-dependent density functional theory usually provides a good description of low-lying excitations of molecules. In the present work, the capability of the adiabatic nonempirical…

Materials Science · Physics 2009-11-13 Jianmin Tao , Sergei Tretiak , Jian-Xin Zhu

We recently showed that the DFT+U approach with a linear-response U yields adiabatic energy differences biased towards high spin [Mariano et al. J. Chem. Theory Comput. 2020, 16, 6755-6762]. Such bias is removed here by employing a…

Strongly Correlated Electrons · Physics 2021-01-19 Lorenzo A. Mariano , Bess Vlaisavljevich , Roberta Poloni

A model is developed, based on the density functional perturbation theory and the inverse Kohn-Sham method, that can be used to improve relativistic nuclear energy density functionals towards an exact but unknown Kohn-Sham…

Nuclear Theory · Physics 2021-04-28 Giacomo Accorto , Tomoya Naito , Haozhao Liang , Tamara Niksic , Dario Vretenar

In the quest for low power, bio-inspired computation both memristive and memcapacitive-based Artificial Neural Networks (ANN) have been the subjects of increasing focus for hardware implementation of neuromorphic computing. One step…

Neural and Evolutionary Computing · Computer Science 2022-06-22 Sachin Maheshwari , Alexander Serb , Christos Papavassiliou , Themistoklis Prodromakis

A systematic way of improving exchange-correlation energy functionals of density functional theory has been to make them satisfy more and more exact relations. Starting from the initial GGA functionals, this has culminated into the recently…

Chemical Physics · Physics 2017-10-11 Rabeet Singh , Manoj K. Harbola

We introduce an interpretable deep learning framework that predicts the cohesive energy of transition-metal alloys (TMAs) by embedding cohesion theory within graph neural networks (GNNs). Beyond accurate prediction of cohesive energy, a key…

Materials Science · Physics 2025-09-11 Yang Huang , Shih-Han Wang , Shuyi Cao , Luke E. K. Achenie , Hongliang Xin

Recent advancements in exchange-correlation functionals within density functional theory highlight the need for rigorous validation across diverse types of materials properties. In this study, we assess the performance of the newly…

Materials Science · Physics 2025-04-17 Nafise Rezaei , Mojtaba Alaei , Artem R. Oganov

Modern density functional theory (DFT) calculations employ the Kohn-Sham (KS) system of non-interacting electrons as a reference, with all complications buried in the exchange-correlation energy (Exc). The adiabatic connection formula gives…

Other Condensed Matter · Physics 2009-10-02 Zhenfei Liu , Kieron Burke

We present calculations of the correlation energies of crystalline solids and isolated systems within the adiabatic-connection fluctuation-dissipation formulation of density-functional theory. We perform a quantitative comparison of a set…

Materials Science · Physics 2016-07-29 Christopher E. Patrick , Kristian S. Thygesen

We performed density functional calculations to estimate the formation energies of intermetallic alloys. We used two semilocal approximations, the generalized gradient approximation (GGA) by Perdew-Burke-Ernzerhof (PBE) and the strongly…

Materials Science · Physics 2020-11-25 Niraj K. Nepal , Santosh Adhikari , Bimal Neupane , Adrienn Ruzsinszky

This paper presents a novel Riemannian conjugate gradient method for the Kohn-Sham energy minimization problem in density functional theory (DFT), with a focus on non-metallic crystal systems. We introduce an energy-adaptive metric that…

Numerical Analysis · Mathematics 2025-03-21 Daniel Peterseim , Jonas Püschel , Tatjana Stykel