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RelatedMaterial
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destroy: {"material_type"=>"Article", "availability"=>nil, "link"=>"https://arxiv.org/abs/1805.09433", "uri"=>"", "uri_type"=>"", "citation"=>"Karigerasi, Manohar H., Wagner, Lucas K., Shoemaker, Daniel P. Uncovering anisotropic magnetic phases via fast dimensionality analysis. arXiv:1805.09433", "dataset_id"=>568, "selected_type"=>"Article", "datacite_list"=>"", "note"=>"", "feature"=>false}
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2025-01-08T23:48:50Z
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RelatedMaterial
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update: {"uri"=>[nil, ""], "uri_type"=>[nil, ""], "datacite_list"=>[nil, ""], "note"=>[nil, ""], "feature"=>[nil, false]}
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2024-02-01T18:04:01Z
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RelatedMaterial
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update: {"uri"=>[nil, "http://shoemaker.matse.illinois.edu/magnetic-dimensionality/"], "uri_type"=>[nil, "URL"], "datacite_list"=>[nil, ""], "note"=>[nil, ""], "feature"=>[nil, false]}
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2024-02-01T18:04:01Z
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RelatedMaterial
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update: {"uri"=>[nil, "https://github.com/Manohar-94/magnetic_dimensionality_toolkit"], "uri_type"=>[nil, "URL"], "datacite_list"=>[nil, "IsSupplementedBy"], "note"=>[nil, ""], "feature"=>[nil, false]}
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2024-02-01T18:04:01Z
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Dataset
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update: {"version_comment"=>[nil, ""]}
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2024-02-01T18:04:01Z
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RelatedMaterial
|
update: {"link"=>["http://arxiv.org", "https://arxiv.org/abs/1805.09433"], "citation"=>["Karigerasi, Manohar H., Wagner, Lucas K., Shoemaker, Daniel P. Uncovering anisotropic magnetic phases via fast dimensionality analysis. arXiv (to be submitted)", "Karigerasi, Manohar H., Wagner, Lucas K., Shoemaker, Daniel P. Uncovering anisotropic magnetic phases via fast dimensionality analysis. arXiv:1805.09433"]}
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2018-05-25T03:05:12Z
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RelatedMaterial
|
update: {"citation"=>["Uncovering anisotropic magnetic phases via fast dimensionality analysis\r\nManohar H. Karigerasi, Lucas K. Wagner, Daniel P. Shoemaker (to be submitted on arxiv)", "Karigerasi, Manohar H., Wagner, Lucas K., Shoemaker, Daniel P. Uncovering anisotropic magnetic phases via fast dimensionality analysis. arXiv (to be submitted)"]}
|
2018-05-21T21:12:09Z
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Dataset
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update: {"description"=>["This dataset contains bonding networks and tolerance ranges for geometric magnetic dimensionality. The data can be searched in the html frontend above, code obtained at the GitHub repository, or the raw data can be downloaded as csv below. The csv is semicolon-delimited since some fields contain multiple comma-separated values.", "This dataset contains bonding networks and tolerance ranges for geometric magnetic dimensionality. The data can be searched in the html frontend above, code obtained at the GitHub repository, or the raw data can be downloaded as csv below. The csv data contains the results of 42520 compounds (unique icsd_code) from ICSD FindIt v3.5.0. The csv is semicolon-delimited since some fields contain multiple comma-separated values."]}
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2018-05-21T21:12:09Z
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