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Metal-organic frameworks (MOFs) are porous materials composed of metal ions and organic linkers. Due to their chemical diversity, MOFs can support a broad range of applications in chemical separations. However, the vast amount of structural…

Accurate computational predictions of metal-organic frameworks (MOFs) and their properties is crucial for discovering optimal compositions and applying them in relevant technological areas. This work benchmarks density functional theory…

Materials Science · Physics 2025-03-11 Joshua Edzards , Julia Santana Andreo , Holger-Dietrich Saßnick , Caterina Cocchi

We present an efficient and systematically convergent approach to all-electron real-time time-dependent density functional theory (TDDFT) calculations using a mixed basis, termed as enriched finite element (EFE) basis. The EFE basis…

Chemical Physics · Physics 2022-10-27 Bikash Kanungo , Nelson D. Rufus , Vikram Gavini

Fitting a theoretical model to experimental data in a Bayesian manner using Markov chain Monte Carlo typically requires one to evaluate the model thousands (or millions) of times. When the model is a slow-to-compute physics simulation,…

Machine Learning · Statistics 2022-08-25 Steven Stetzler , Michael Grosskopf , Earl Lawrence

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…

Density-functional perturbation theory (DFPT) is nowadays the method of choice for the accurate computation of linear and non-linear response properties of materials from first principles. A notable advantage of DFPT over alternative…

Materials Science · Physics 2019-06-19 Miquel Royo , Massimiliano Stengel

Local density approximation (LDA) to the density functional theory (DFT) has continuous derivative of total energy as a number of electrons function and continuous exchange-correlation potential, while in exact DFT both should be…

Strongly Correlated Electrons · Physics 2010-06-28 V. I. Anisimov , A. V. Kozhevnikov , M. A. Korotin , A. V. Lukoyanov , D. A. Khafizullin

The standard technique for sub-pixel estimation of atom positions from atomic resolution scanning transmission electron microscopy images relies on fitting intensity maxima or minima with a two-dimensional Gaussian function. While this is a…

Materials Science · Physics 2020-01-28 Debangshu Mukherjee , Leixin Miao , Greg Stone , Nasim Alem

By partitioning the electron density into subsystem contributions, the Frozen Density Embedding (FDE) formulation of subsystem DFT has recently emerged as a powerful tool for reducing the computational scaling of Kohn--Sham DFT. To date,…

Materials Science · Physics 2015-06-22 Alessandro Genova , Davide Ceresoli , Michele Pavanello

Recent advances in communications, mobile computing, and artificial intelligence have greatly expanded the application space of intelligent distributed sensor networks. This in turn motivates the development of generalized Bayesian…

Robotics · Computer Science 2013-08-15 Nisar Ahmed , Tsung-Lin Yang , Mark Campbell

Bridging the gap between first principles methods and empirical schemes, the density functional based tight-binding method (DFTB) has become a versatile tool in predictive atomistic simulations over the past years. One of the major…

Materials Science · Physics 2015-04-02 Vitalij Lutsker , Balint Aradi , Thomas A. Niehaus

Orbital-free density functional theory (OF-DFT) is a promising method for large-scale quantum mechanics simulation as it provides a good balance of accuracy and computational cost. Its applicability to large-scale simulations has been aided…

Molecule-optimized basis sets, based on approximate natural orbitals, are developed for accelerating the convergence of quantum calculations with strongly correlated (multi-referenced) electrons. We use a low-cost approximate solution of…

Chemical Physics · Physics 2014-02-12 Gergely Gidofalvi , David A. Mazziotti

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…

One of the open problems in nuclear structure is how to predict properties of finite nuclei from the knowledge of a bare nucleon-nucleon interaction of the meson-exchange type. We point out that a promising starting point consists in…

Nuclear Theory · Physics 2014-11-20 Nguyen Van Giai , Brett V. Carlson , Zhongyu Ma , Hermann Wolter

We present a $GW$ space-time algorithm for periodic systems in a Gaussian basis including spin-orbit coupling. We employ lattice summation to compute the irreducible density response and the self-energy, while we employ $k$-point sampling…

Materials databases built from calculations based on density functional approximations play an important role in the discovery of materials with improved properties. Most databases thus constructed rely on the generalized gradient…

Materials Science · Physics 2025-04-30 Akhil S. Nair , Lucas Foppa , Matthias Scheffler

We present an accurate, efficient and massively parallel finite-element code, DFT-FE, for large-scale ab-initio calculations (reaching $\sim 100,000$ electrons) using Kohn-Sham density functional theory (DFT). DFT-FE is based on a local…

Computational Physics · Physics 2020-01-08 Phani Motamarri , Sambit Das , Shiva Rudraraju , Krishnendu Ghosh , Denis Davydov , Vikram Gavini

Orbital-free density functional theory (OFDFT) offers a true realization of the Hohenberg-Kohn theorems, enabling full quantum-mechanical studies of electronic systems based solely on electron densities. However, OFDFT remains limited by…

Chemical Physics · Physics 2025-05-08 Siwoo Lee , Adji Bousso Dieng

Projection-based embedding provides a simple, robust, and accurate approach for describing a small part of a chemical system at the level of a correlated wavefunction method while the remainder of the system is described at the level of…

Chemical Physics · Physics 2019-08-21 Sebastian J. R. Lee , Feizhi Ding , Frederick R. Manby , Thomas F. Miller
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