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The preferred spin orientation of a magnetic ion can be predicted on the basis of density functional theory (DFT) calculations including electron correlation and spin-orbit coupling (SOC). However, most chemists and physicists are unaware…

Strongly Correlated Electrons · Physics 2015-12-31 Myung-Hwan Whangbo , Elijah E. Gordon , Hongjun Xiang , Hyun-Joo Koo , Changhoon Lee

Machine learning potentials (MLPs) have significantly advanced global crystal structure prediction by enabling efficient and accurate property evaluations. In this study, global structure searches are performed for 11 bismuth-based binary…

Materials Science · Physics 2025-11-10 Hayato Wakai , Shintaro Ishiwata , Atsuto Seko

We investigate the structural conditions for metamagnetism in MnP and related materials using Density Functional Theory. A magnetic stability plot is constructed taking into account the two shortest Mn-Mn distances. We find that a…

Materials Science · Physics 2010-06-23 Z. Gercsi , K. G. Sandeman

We present a systematic high-throughput density-functional-theory investigation of the structural and magnetic stability of 312 substitutional compounds in the magnetic kagome AT6X6 family. Our screening confirms the stability of many…

Materials Science · Physics 2026-05-05 Shiya Chen , Zhen Zhang , Vladimir Antropov , Yang Sun

Total energies of crystal structures can be calculated to high precision using quantum-based density functional theory (DFT) methods, but the calculations can be time consuming and scale badly with system size. Cluster expansions of total…

Materials Science · Physics 2015-12-31 Qin Gao , Sanxi Yao , Jeff Schneider , Michael Widom

Machine learning potentials (MLPs) have become indispensable for conducting accurate large-scale atomistic simulations and for the efficient prediction of crystal structures. Polynomial MLPs, defined by polynomial rotational invariants,…

Materials Science · Physics 2024-08-05 Atsuto Seko

The shell-model-like approach (SLAP) based on cranking covariant density functional theory (CDFT) with a separable pairing force is developed. The developed cranking CDFT-SLAP with separable pairing force is applied to investigate the…

Nuclear Theory · Physics 2020-05-13 BinWu Xiong

We present conditional probability (CP) density functional theory (DFT) as a formally exact theory. In essence, CP-DFT determines the ground-state energy of a system by finding the CP density from a series of independent Kohn-Sham (KS) DFT…

Chemical Physics · Physics 2022-06-28 Ryan Pederson , Jielun Chen , Steven R. White , Kieron Burke

Expansions through the 24th order at high-temperature and up to 11th order at low-temperature are derived for the main observables of the Blume-Capel model on bipartite lattices (sq, sc and bcc) in 2d and 3d with various values of the spin…

Statistical Mechanics · Physics 2018-05-24 P. Butera , M. Pernici

We model the stabilization of clusters and lattices of cuboidal particles with long-ranged magnetic dipolar and short-ranged surface interactions. Two realistic systems were considered: one with magnetization orientated in the [001]…

Soft Condensed Matter · Physics 2020-09-09 Igor Stankovic , Luis Lizardi , Carlos Garcia

The prediction of energetically stable crystal structures formed by a given chemical composition is a central problem in solid-state physics. In principle, the crystalline state of assembled atoms can be determined by optimizing the energy…

Materials Science · Physics 2022-06-01 Minoru Kusaba , Chang Liu , Ryo Yoshida

Brain-inspired computing architectures attempt to emulate the computations performed in the neurons and the synapses in human brain. Memristors with continuously tunable resistances are ideal building blocks for artificial synapses. Through…

In this paper a composed A+B magnetic system, with spins J_A=2 and J_B=3/2, is considered within the mean-field approximation, in the framework of Tsallis nonextensive statistics. Our motivation is twofold: (1) to approach the existing…

Statistical Mechanics · Physics 2009-09-24 F. A. R. Navarro , M. S. Reis , E. K Lenzi , I. S. Olivera

Crystal structure prediction (CSP) is now increasingly used in the discovery of novel materials with applications in diverse industries. However, despite decades of developments, the problem is far from being solved. With the progress of…

Materials Science · Physics 2023-07-13 Lai Wei , Qin Li , Sadman Sadeed Omee , Jianjun Hu

We have considered clusters of like spin in the Q-Potts model, the spin Potts clusters. Using Monte Carlo simulations, we studied these clusters on a square lattice with periodic boundary conditions for values of Q in [1,4]. We continue the…

Statistical Mechanics · Physics 2022-03-09 Marco Picco , Raoul Santachiara

Density functional theory (DFT) is the de facto approach for predicting self-consistent-field electronic structures of ground-state configurations of complex atoms, molecules, and solids and providing their property data for materials…

Materials Science · Physics 2024-01-30 Zi-Kui Liu

In this paper, we carry out a pilot parameter exploration for the collision-induced magnetic reconnection (CMR) mechanism that forms filamentary molecular clouds. Following Kong et al. (2021), we utilize Athena++ to model CMR in the context…

Astrophysics of Galaxies · Physics 2023-04-19 Shuo Kong , Volker Ossenkopf-Okada , Héctor G. Arce , Ralf S. Klessen , Duo Xu

The accurate resolution of the chemical properties of strongly correlated systems, such as biradicals, requires the use of electronic structure theories that account for both multi-reference as well as dynamic correlation effects. A variety…

Chemical Physics · Physics 2023-01-03 Jan-Niklas Boyn , David A. Mazziotti

Density functional theory (DFT) provides convenient electronic structure methods for the study of molecular systems and materials. Regular Kohn-Sham DFT calculations rely on unitary transformations to determine the ground-state electronic…

Chemical Physics · Physics 2022-10-10 Greta Jacobson , Juan M. Marmolejo-Tejada , Martín A. Mosquera

Frustrated triangular molecular magnets (MMs) with anti-ferromagnetic ground states (GS) are an important class of magnetic systems with potential applications in quantum information processing. The two-fold degenerate GS of these…

Mesoscale and Nanoscale Physics · Physics 2025-01-20 M. F. Islam , Kushantha P. K. Withanage , C. M. Canali , Mark R. Pederson
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