Dataset on the enthalpy of mixing in binary liquids
This dataset contains: (1) "Dataset" folder - Data on the enthalpy of mixing collected in 375 binary liquids from Calphad modeling in composition domains where the models are supported by experimental measurements. Metadata ("Metadata.csv") and explanation of the data quality ran...
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| creator | Deffrennes, Guillaume Hallstedt, Bengt Abe, Taichi Bizot, Quentin Fischer, Evelyne Joubert, Jean-Marc Terayama, Group Tamura, Ryo |
| description | This dataset contains:
(1) "Dataset" folder - Data on the enthalpy of mixing collected in 375 binary liquids from Calphad modeling in composition domains where the models are supported by experimental measurements. Metadata ("Metadata.csv") and explanation of the data quality ranking ("Readme_Metadata.txt") are given in the root folder.
(2) "Predictions" folder - Machine learning predictions of this property given as Redlich-Kister polynomials in the 2415 binary systems generated by 70 elements. The predictions are also compared with those of the Miedema model in tables and figures where data are also plotted when available.
For more information and to use this dataset, please refer to this manuscript under review for publication:
G. Deffrennes, B. Hallstedt, T. Abe, Q. Bizot, E. Fischer, J-M. Joubert, K. Terayama, and R. Tamura, Data-driven study of the enthalpy of mixing in the liquid phase, arXiv:2406.11004v1 [cond-mat.mtrl-sci]. |
| doi_str_mv | 10.17632/6wt6t9kswt.1 |
| format | Dataset |
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(1) "Dataset" folder - Data on the enthalpy of mixing collected in 375 binary liquids from Calphad modeling in composition domains where the models are supported by experimental measurements. Metadata ("Metadata.csv") and explanation of the data quality ranking ("Readme_Metadata.txt") are given in the root folder.
(2) "Predictions" folder - Machine learning predictions of this property given as Redlich-Kister polynomials in the 2415 binary systems generated by 70 elements. The predictions are also compared with those of the Miedema model in tables and figures where data are also plotted when available.
For more information and to use this dataset, please refer to this manuscript under review for publication:
G. Deffrennes, B. Hallstedt, T. Abe, Q. Bizot, E. Fischer, J-M. Joubert, K. Terayama, and R. Tamura, Data-driven study of the enthalpy of mixing in the liquid phase, arXiv:2406.11004v1 [cond-mat.mtrl-sci].</description><identifier>DOI: 10.17632/6wt6t9kswt.1</identifier><language>eng</language><publisher>Mendeley Data</publisher><subject>Enthalpy ; Liquid ; Liquid Alloy ; Machine Learning ; Mixing ; Phase Diagram</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-4314-2266 ; 0000-0002-0349-358X ; 0000-0001-7266-1850 ; 0000-0001-5959-7030 ; 0000-0003-3914-248X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>780,1894</link.rule.ids><linktorsrc>$$Uhttps://commons.datacite.org/doi.org/10.17632/6wt6t9kswt.1$$EView_record_in_DataCite.org$$FView_record_in_$$GDataCite.org$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Deffrennes, Guillaume</creatorcontrib><creatorcontrib>Hallstedt, Bengt</creatorcontrib><creatorcontrib>Abe, Taichi</creatorcontrib><creatorcontrib>Bizot, Quentin</creatorcontrib><creatorcontrib>Fischer, Evelyne</creatorcontrib><creatorcontrib>Joubert, Jean-Marc</creatorcontrib><creatorcontrib>Terayama, Group</creatorcontrib><creatorcontrib>Tamura, Ryo</creatorcontrib><title>Dataset on the enthalpy of mixing in binary liquids</title><description>This dataset contains:
(1) "Dataset" folder - Data on the enthalpy of mixing collected in 375 binary liquids from Calphad modeling in composition domains where the models are supported by experimental measurements. Metadata ("Metadata.csv") and explanation of the data quality ranking ("Readme_Metadata.txt") are given in the root folder.
(2) "Predictions" folder - Machine learning predictions of this property given as Redlich-Kister polynomials in the 2415 binary systems generated by 70 elements. The predictions are also compared with those of the Miedema model in tables and figures where data are also plotted when available.
For more information and to use this dataset, please refer to this manuscript under review for publication:
G. Deffrennes, B. Hallstedt, T. Abe, Q. Bizot, E. Fischer, J-M. Joubert, K. Terayama, and R. Tamura, Data-driven study of the enthalpy of mixing in the liquid phase, arXiv:2406.11004v1 [cond-mat.mtrl-sci].</description><subject>Enthalpy</subject><subject>Liquid</subject><subject>Liquid Alloy</subject><subject>Machine Learning</subject><subject>Mixing</subject><subject>Phase Diagram</subject><fulltext>true</fulltext><rsrctype>dataset</rsrctype><creationdate>2024</creationdate><recordtype>dataset</recordtype><sourceid>PQ8</sourceid><recordid>eNpjYBA1NNAzNDczNtI3Ky8xK7HMLi4v0TPkZDB2SSxJLE4tUcjPUyjJSFVIzSvJSMwpqFTIT1PIzazIzEtXyMxTSMrMSyyqVMjJLCzNTCnmYWBNS8wpTuWF0twMum6uIc4euilAs5IzS1LjC4oyc4Ea4g0N4sGWxiMsjTc0JlU9APZNPH0</recordid><startdate>20240910</startdate><enddate>20240910</enddate><creator>Deffrennes, Guillaume</creator><creator>Hallstedt, Bengt</creator><creator>Abe, Taichi</creator><creator>Bizot, Quentin</creator><creator>Fischer, Evelyne</creator><creator>Joubert, Jean-Marc</creator><creator>Terayama, Group</creator><creator>Tamura, Ryo</creator><general>Mendeley Data</general><scope>DYCCY</scope><scope>PQ8</scope><orcidid>https://orcid.org/0000-0002-4314-2266</orcidid><orcidid>https://orcid.org/0000-0002-0349-358X</orcidid><orcidid>https://orcid.org/0000-0001-7266-1850</orcidid><orcidid>https://orcid.org/0000-0001-5959-7030</orcidid><orcidid>https://orcid.org/0000-0003-3914-248X</orcidid></search><sort><creationdate>20240910</creationdate><title>Dataset on the enthalpy of mixing in binary liquids</title><author>Deffrennes, Guillaume ; Hallstedt, Bengt ; Abe, Taichi ; Bizot, Quentin ; Fischer, Evelyne ; Joubert, Jean-Marc ; Terayama, Group ; Tamura, Ryo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-datacite_primary_10_17632_6wt6t9kswt_13</frbrgroupid><rsrctype>datasets</rsrctype><prefilter>datasets</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Enthalpy</topic><topic>Liquid</topic><topic>Liquid Alloy</topic><topic>Machine Learning</topic><topic>Mixing</topic><topic>Phase Diagram</topic><toplevel>online_resources</toplevel><creatorcontrib>Deffrennes, Guillaume</creatorcontrib><creatorcontrib>Hallstedt, Bengt</creatorcontrib><creatorcontrib>Abe, Taichi</creatorcontrib><creatorcontrib>Bizot, Quentin</creatorcontrib><creatorcontrib>Fischer, Evelyne</creatorcontrib><creatorcontrib>Joubert, Jean-Marc</creatorcontrib><creatorcontrib>Terayama, Group</creatorcontrib><creatorcontrib>Tamura, Ryo</creatorcontrib><collection>DataCite (Open Access)</collection><collection>DataCite</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Deffrennes, Guillaume</au><au>Hallstedt, Bengt</au><au>Abe, Taichi</au><au>Bizot, Quentin</au><au>Fischer, Evelyne</au><au>Joubert, Jean-Marc</au><au>Terayama, Group</au><au>Tamura, Ryo</au><format>book</format><genre>unknown</genre><ristype>DATA</ristype><title>Dataset on the enthalpy of mixing in binary liquids</title><date>2024-09-10</date><risdate>2024</risdate><abstract>This dataset contains:
(1) "Dataset" folder - Data on the enthalpy of mixing collected in 375 binary liquids from Calphad modeling in composition domains where the models are supported by experimental measurements. Metadata ("Metadata.csv") and explanation of the data quality ranking ("Readme_Metadata.txt") are given in the root folder.
(2) "Predictions" folder - Machine learning predictions of this property given as Redlich-Kister polynomials in the 2415 binary systems generated by 70 elements. The predictions are also compared with those of the Miedema model in tables and figures where data are also plotted when available.
For more information and to use this dataset, please refer to this manuscript under review for publication:
G. Deffrennes, B. Hallstedt, T. Abe, Q. Bizot, E. Fischer, J-M. Joubert, K. Terayama, and R. Tamura, Data-driven study of the enthalpy of mixing in the liquid phase, arXiv:2406.11004v1 [cond-mat.mtrl-sci].</abstract><pub>Mendeley Data</pub><doi>10.17632/6wt6t9kswt.1</doi><orcidid>https://orcid.org/0000-0002-4314-2266</orcidid><orcidid>https://orcid.org/0000-0002-0349-358X</orcidid><orcidid>https://orcid.org/0000-0001-7266-1850</orcidid><orcidid>https://orcid.org/0000-0001-5959-7030</orcidid><orcidid>https://orcid.org/0000-0003-3914-248X</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | DOI: 10.17632/6wt6t9kswt.1 |
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| language | eng |
| recordid | cdi_datacite_primary_10_17632_6wt6t9kswt_1 |
| source | DataCite |
| subjects | Enthalpy Liquid Liquid Alloy Machine Learning Mixing Phase Diagram |
| title | Dataset on the enthalpy of mixing in binary liquids |
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