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Title: Uncovering anisotropic magnetic phases via fast dimensionality analysis

Abstract

A quantitative geometric predictor for the dimensionality of magnetic interactions is presented. This predictor is based on networks of superexchange interactions and can be quickly calculated for crystalline compounds of arbitrary chemistry, occupancy, or symmetry. The resulting data are useful for classifying structural families of magnetic compounds. We have examined compounds from a demonstration set of 42,520 materials with 3d transition metal cations. The predictor reveals trends in magnetic interactions that are often not apparent from the space group of the compounds, such as triclinic or monoclinic compounds that are strongly 2D. We present speci c cases where the predictor identi es compounds that should exhibit competition between 1D and 2D interactions, and how the predictor can be used to identify sparsely-populated regions of chemical space with as-yet-unexplored topologies of speci c 3d magnetic cations. The predictor can be accessed for the full list of compounds using a searchable frontend, and further information on the connectivity, symmetry, valence, and cation-anion and cation-cation coordination can be freely exported.

Authors:
 [1];  [2];  [1]
  1. Univ. of Illinois at Urbana-Champaign, IL (United States). Dept. of Materials Science and Engineering
  2. Univ. of Illinois at Urbana-Champaign, IL (United States)
Publication Date:
Research Org.:
Energy Frontier Research Centers (EFRC) (United States). Center for Emergent Superconductivity (CES); Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1566383
Alternate Identifier(s):
OSTI ID: 1468841
Grant/Contract Number:  
[AC02-98CH10886]
Resource Type:
Accepted Manuscript
Journal Name:
Physical Review Materials
Additional Journal Information:
[ Journal Volume: 2; Journal Issue: 9]; Journal ID: ISSN 2475-9953
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; phonons; thermal conductivity; energy storage (including batteries and capacitors); superconductivity; defects; spin dynamics

Citation Formats

Karigerasi, Manohar H., Wagner, Lucas K., and Shoemaker, Daniel P. Uncovering anisotropic magnetic phases via fast dimensionality analysis. United States: N. p., 2018. Web. doi:10.1103/physrevmaterials.2.094403.
Karigerasi, Manohar H., Wagner, Lucas K., & Shoemaker, Daniel P. Uncovering anisotropic magnetic phases via fast dimensionality analysis. United States. doi:10.1103/physrevmaterials.2.094403.
Karigerasi, Manohar H., Wagner, Lucas K., and Shoemaker, Daniel P. Tue . "Uncovering anisotropic magnetic phases via fast dimensionality analysis". United States. doi:10.1103/physrevmaterials.2.094403. https://www.osti.gov/servlets/purl/1566383.
@article{osti_1566383,
title = {Uncovering anisotropic magnetic phases via fast dimensionality analysis},
author = {Karigerasi, Manohar H. and Wagner, Lucas K. and Shoemaker, Daniel P.},
abstractNote = {A quantitative geometric predictor for the dimensionality of magnetic interactions is presented. This predictor is based on networks of superexchange interactions and can be quickly calculated for crystalline compounds of arbitrary chemistry, occupancy, or symmetry. The resulting data are useful for classifying structural families of magnetic compounds. We have examined compounds from a demonstration set of 42,520 materials with 3d transition metal cations. The predictor reveals trends in magnetic interactions that are often not apparent from the space group of the compounds, such as triclinic or monoclinic compounds that are strongly 2D. We present speci c cases where the predictor identi es compounds that should exhibit competition between 1D and 2D interactions, and how the predictor can be used to identify sparsely-populated regions of chemical space with as-yet-unexplored topologies of speci c 3d magnetic cations. The predictor can be accessed for the full list of compounds using a searchable frontend, and further information on the connectivity, symmetry, valence, and cation-anion and cation-cation coordination can be freely exported.},
doi = {10.1103/physrevmaterials.2.094403},
journal = {Physical Review Materials},
number = [9],
volume = [2],
place = {United States},
year = {2018},
month = {9}
}

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