GPTArticleExtractor: An Automated Workflow for Magnetic Material Database Construction
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arXiv
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| Hauptverfasser: | , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866911755306795008 |
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| author | Zhang, Yibo Itani, Suman Khanal, Kamal Okyere, Emmanuel Smith, Gavin Takahashi, Koichiro Zang, Jiadong |
| author_facet | Zhang, Yibo Itani, Suman Khanal, Kamal Okyere, Emmanuel Smith, Gavin Takahashi, Koichiro Zang, Jiadong |
| contents | A comprehensive database of magnetic materials is valuable for researching the properties of magnetic materials and discovering new ones. This article introduces a novel workflow that leverages large language models for extracting key information from scientific literature. From 22,120 articles in the Journal of Magnetism and Magnetic Materials, a database containing 2,035 magnetic materials was automatically generated, with ferromagnetic materials constituting 76% of the total. Each entry in the database includes the material's chemical compounds, as well as related structures (space group, crystal structure) and magnetic temperatures (Curie, N'eel, and other transitional temperatures). To ensure data accuracy, we meticulously compared each entry in the database against the original literature, verifying the precision and reliability of each entry. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_05875 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | GPTArticleExtractor: An Automated Workflow for Magnetic Material Database Construction Zhang, Yibo Itani, Suman Khanal, Kamal Okyere, Emmanuel Smith, Gavin Takahashi, Koichiro Zang, Jiadong Materials Science A comprehensive database of magnetic materials is valuable for researching the properties of magnetic materials and discovering new ones. This article introduces a novel workflow that leverages large language models for extracting key information from scientific literature. From 22,120 articles in the Journal of Magnetism and Magnetic Materials, a database containing 2,035 magnetic materials was automatically generated, with ferromagnetic materials constituting 76% of the total. Each entry in the database includes the material's chemical compounds, as well as related structures (space group, crystal structure) and magnetic temperatures (Curie, N'eel, and other transitional temperatures). To ensure data accuracy, we meticulously compared each entry in the database against the original literature, verifying the precision and reliability of each entry. |
| title | GPTArticleExtractor: An Automated Workflow for Magnetic Material Database Construction |
| topic | Materials Science |
| url | https://arxiv.org/abs/2401.05875 |