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Related papers: Ab initio Random Structure Searching

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Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here we…

We have studied intrinsic defect complexes in In$_2$O$_3$ using ab initio random structure searching (AIRSS). Our first-principles density-functional-theory calculations predict the thermodynamic stability of several novel defect…

Materials Science · Physics 2016-09-16 Jamie M. Wynn , Richard J. Needs , Andrew J. Morris

We develop a materials descriptor based on the electronic density of states and investigate the similarity of materials based on it. As an application example, we study the Computational 2D Materials Database that hosts thousands of…

Materials Science · Physics 2022-01-07 Martin Kuban , Santiago Rigamonti , Markus Scheidgen , Claudia Draxl

We present a novel approach for finding and evaluating structural models of small metallic nanoparticles. Rather than fitting a single model with many degrees of freedom, the approach algorithmically builds libraries of nanoparticle…

The calculation of electronic properties of materials is an important task of solid state theory, albeit particularly difficult if electronic correlations are strong, for example in transition metals, their oxides and in f-electron systems.…

Strongly Correlated Electrons · Physics 2009-09-29 K. Held

In this paper, we employ evolutionary algorithm along with the full-potential density functional theory (DFT) computations to perform a comprehensive search for the stable structures of stoichiometric (WS2)n nano-clusters (n=1-9), within…

Nuclear density functional theory (DFT) is one of the main theoretical tools used to study the properties of heavy and superheavy elements, or to describe the structure of nuclei far from stability. While on-going efforts seek to better…

Nuclear Theory · Physics 2015-12-23 N. Schunck , J. D. McDonnell , D. Higdon , J. Sarich , S. M. Wild

Electrides are exotic compounds in which excess electrons occupy interstitial regions of the crystal lattice and serve as anions, exhibiting exceptional properties such as low work function, high electron mobility, and strong catalytic…

Materials Science · Physics 2026-01-30 Shuo Tao , Qiang Zhu

Active learning has been increasingly applied to screening functional materials from existing materials databases with desired properties. However, the number of known materials deposited in the popular materials databases such as ICSD and…

The development of quantitative models for radiation damage effects in iron, iron alloys and steels, particularly for the high temperature properties of the alloys, requires understanding of magnetic interactions, which control the phase…

Materials Science · Physics 2015-06-17 D. Nguyen-Manh , Pui-Wai Ma , M. Yu. Lavrentiev , S. L. Dudarev

Over many years, computational simulations based on Density Functional Theory (DFT) have been used extensively to study many different materials at the atomic scale. However, its application is restricted by system size, leaving a number of…

Mesoscale and Nanoscale Physics · Physics 2018-12-05 Carlos Romero-Muñiz , Ayako Nakata , Pablo Pou , David R. Bowler , Tsuyoshi Miyazaki , Rubén Pérez

The electronic structure of a material fundamentally determines its underlying physical, and by extension, its functional properties. Consequently, the ability to identify or generate materials with desired electronic properties would…

Materials Science · Physics 2025-04-09 Shuyi Jia , Panchapakesan Ganesh , Victor Fung

Knowledge of the atomic geometry of a surface is a prerequisite for any detailed understanding of the surface's electronic structure and chemical properties. Previous studies have convincingly demonstrated that density functional theory…

Materials Science · Physics 2007-05-23 C. Stampfl , M. Scheffler

The block diagonal structure of an affinity matrix is a commonly desired property in cluster analysis because it represents clusters of feature vectors by non-zero coefficients that are concentrated in blocks. However, recovering a block…

Machine Learning · Computer Science 2023-12-05 Aylin Tastan , Michael Muma , Abdelhak M. Zoubir

We propose a new molecular simulation framework that combines the transferability, robustness and chemical flexibility of an ab initio method with the accuracy and efficiency of a machine learned force field. The key to achieve this mix is…

Computational Physics · Physics 2020-01-08 Sebastian Dick , Marivi Fernandez-Serra

Disordered elemental semiconductors, most notably a-C and a-Si, are ubiquitous in a myriad of different applications. These exploit their unique mechanical and electronic properties. In the past couple of decades, density functional theory…

Materials Science · Physics 2023-03-14 Miguel A. Caro

The stopping site of the muon in a muon-spin relaxation experiment ({\mu}+SR) is in general unknown. There are some techniques that can be used to guess the muon stopping site, but they often rely on approximations and are not generally…

Materials Science · Physics 2018-05-21 Leandro Liborio , Simone Sturniolo , Dominik Jochym

We present a comparative electronic structure study using DFT and various beyond-DFT (DFT+$U$, $G_0W_0$, DFT+DMFT) methods for ferromagnetic Iron (Fe) to find better approach for describing the spectral properties of correlated magnetic…

Strongly Correlated Electrons · Physics 2021-01-01 Antik Sihi , Sudhir K. Pandey

Reliable calculations of the structure of heavy elements are crucial to address fundamental science questions such as the origin of the elements in the universe. Applications relevant for energy production, medicine, or national security…

Determining the atomic-level structure of crystalline solids is critically important across a wide array of scientific disciplines. The challenges associated with obtaining samples suitable for single-crystal diffraction, coupled with the…

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