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We scrutinize the accuracy of the pseudopotential approximation in density-functional theory (DFT) calculations of surfaces by systematically comparing to results obtained within a full-potential setup. As model system we choose the CO…

Materials Science · Physics 2007-05-23 Adam Kiejna , Georg Kresse , Jutta Rogal , Abir De Sarkar , Karsten Reuter , Matthias Scheffler

Machine learning models for the potential energy of multi-atomic systems, such as the deep potential (DP) model, make possible molecular simulations with the accuracy of quantum mechanical density functional theory, at a cost only…

Recent experiments by Kiritani et al. have revealed a surprisingly high rate of vacancy production during high-speed deformation of thin foils of fcc metals. Virtually no dislocations are seen after the deformation. This is interpreted as…

Materials Science · Physics 2022-11-09 J. Schiøtz , T. Leffers , B. N. Singh

In recent years, machine learning interatomic potentials (MLIPs) have attracted significant attention as a method that enables large-scale, long-time atomistic simulations while maintaining accuracy comparable to electronic structure…

Materials Science · Physics 2025-03-27 Yuta Yoshimoto , Naoki Matsumura , Yuto Iwasaki , Hiroshi Nakao , Yasufumi Sakai

Material characterization in nano-mechanical tests requires precise interatomic potentials for the computation of atomic energies and forces with near-quantum accuracy. For such purposes, we develop a robust neural-network interatomic…

A physically-informed continuum crystal plasticity model is presented to elucidate the deformation mechanisms and dislocation evolution in body-centered-cubic (bcc) tantalum widely used as a key structural material for mechanical and…

Density-functional theory (DFT) has revolutionized computer simulations in chemistry and material science. A faithful implementation of the theory requires self-consistent calculations. However, this effort involves repeatedly diagonalizing…

Quantum Physics · Physics 2023-07-17 Taehee Ko , Xiantao Li , Chunhao Wang

Silicon carbide (SiC) is an essential material for next generation semiconductors and components for nuclear plants. It's applications are strongly dependent on its thermal conductivity, which is highly sensitive to microstructures.…

Materials Science · Physics 2021-10-22 Baoqin Fu , Yandong Sun , Linfeng Zhang , Han Wang , Ben Xu

Nuclear density functional theory (DFT) is the only microscopic, global approach to the structure of atomic nuclei. It is used in numerous applications, from determining the limits of stability to gaining a deep understanding of the…

Nuclear Theory · Physics 2015-02-06 Nicolas Schunck , Jordan D. McDonnell , Jason Sarich , Stefan M. Wild , Dave Higdon

Stochastic and mixed stochastic-deterministic density functional theory (DFT) are promising new approaches for the calculation of the equation-of-state and transport properties in materials under extreme conditions. In the intermediate warm…

Computational Physics · Physics 2023-09-27 Vidushi Sharma , Lee A. Collins , Alexander J. White

We develop a fully coupled theoretical description of dislocation dynamics on deformable crystalline surfaces, using continuum modeling and the amplitude-phase-field crystal (APFC) framework extended to curved geometries. We derive a…

Soft Condensed Matter · Physics 2026-02-17 Marcello De Donno , Luiza Angheluta , Marco Salvalaglio

It has been shown in experiments that self-climb of prismatic dislocation loops by pipe diffusion plays important roles in their dynamical behaviors, e.g., coarsening of prismatic loops upon annealing, as well as the physical and mechanical…

Materials Science · Physics 2019-05-21 Xiaohua Niu , Yejun Gu , Yang Xiang

We present in full detail a newly developed formalism enabling density functional perturbation theory (DFPT) calculations from a DFT+$U$ ground state. The implementation includes ultrasoft pseudopotentials and is valid for both insulating…

Strongly Correlated Electrons · Physics 2020-02-21 Andrea Floris , Iurii Timrov , Burak Himmetoglu , Nicola Marzari , Stefano de Gironcoli , Matteo Cococcioni

Modeling hydrogen diffusion and its absorption in traps is a fundamental first step towards the understanding and prediction of hydrogen embrittlement. In this study, a multiscale approach which includes DFT simulations, OkMC, and…

Materials Science · Physics 2025-12-22 Gonzalo Álvarez , Álvaro Ridruejo , Javier Segurado

A general set of methods is presented for calculating chemical potentials in solid and liquid mixtures using {\em ab initio} techniques based on density functional theory (DFT). The methods are designed to give an {\em ab initio} approach…

Materials Science · Physics 2009-11-07 D. Alfe` , M. J. Gillan , G. D. Price

Electronic structure calculation of atoms and molecules, in the past few decades has largely been dominated by density functional methods. This is primarily due to the fact that this can account for electron correlation effects in a…

Chemical Physics · Physics 2013-07-12 Amlan K. Roy

Gold-Silver (Au-Ag) core-shell nanostructures are gaining importance in stretchable electronics where high tensile and fatigue resistance is of paramount importance. This work proposes the parameterization of a modified embedded atomic…

Smectic liquid crystals are charcterized by layers that have a preferred uniform spacing and vanishing curvature in their ground state. Dislocations in the smectics play an important role in phase nucleation, layer reorientation, and…

Soft Condensed Matter · Physics 2017-06-28 Hillel Aharoni , Thomas Machon , Randall D. Kamien

Molecular-level understanding of the interactions between the constituents of an atomic structure is essential for designing novel materials in various applications. This need goes beyond the basic knowledge of the number and types of…

In this paper, we present a 2D numerical model developed to simulate the dynamics of soft, deformable particles. To accommodate significant particle deformations, the particle surface is represented as a narrow shell composed of mass points…

Computational Physics · Physics 2025-04-01 Yohann Trivino , Vincent Richefeu , Farhang Radjai , Komlanvi Lampoh , Jean-Yves Delenne