| Title: | High entropy alloys database generated with large language model |
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| Authors: | ID Chizhevskiy, Vladimir, Institut "Jožef Stefan" (Author)
ID Cvelbar, Uroš, Institut "Jožef Stefan" (Author)
ID Zavašnik, Janez, Institut "Jožef Stefan" (Author)
ID Nominé, Alexandre, Institut "Jožef Stefan" (Author), et al. |
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| Files: |  URL - Source URL, visit https://www.nature.com/articles/s41597-026-06930-z
 PDF - Presentation file, download (2,01 MB)
MD5: 5A05EBDAFB4B35107FCA04A3D962E91B
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  IJS - Jožef Stefan Institute
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| Abstract: | High entropy alloys (HEAs) represent a promising area in materials science, but systematic analysis of the extensive literature remains a challenge. In this study, we used Natural Language Processing (NLP) techniques to analyze 4,625 scientific articles from a restricted corpus representing publisher-accessible literature, successfully identifying and characterizing 12,427 of different high entropy alloys. Through prompt engineering and experiments with Large Language Models (LLMs), including mamba-transformer hybrid architectures, we developed a structured database that captures important parameters such as alloy compositions, phase numbers and crystallographic structures. In our analysis, we distinguish between theoretical and experimental studies, considering specific methodological details for each category. For theoretical work, we have systematically documented modeling approaches and key computational parameters, while experimental studies are cataloged with their synthesis methods and critical processing conditions. This database represents a large-scale, automated extraction of HEA research data. The accuracy of the data ranges from 78.7% for HEA phase identification to 94.3% for HEA composition. |
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| Keywords: | high-entropy alloys, natural language processing, materials informatics |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 28.08.2025 |
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| Article acceptance date: | 17.02.2026 |
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| Publication date: | 16.04.2026 |
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| Publisher: | Nature Publishing Group |
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| Year of publishing: | 2026 |
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| Number of pages: | str. [1-8] |
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| Numbering: | Vol. 13, [article no.] 612 |
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| Source: | Združeno kraljestvo |
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| PID: | 20.500.12556/DiRROS-29238  |
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| UDC: | 620.1/.2 |
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| ISSN on article: | 2052-4463 |
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| DOI: | 10.1038/s41597-026-06930-z |
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| COBISS.SI-ID: | 271580163 |
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| Copyright: | © The Author(s) 2026 |
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| Note: | Nasl. z nasl. zaslona;
Soavtorji iz Slovenije: Uroš Cvelbar, Janez Zavašnik, Alexandre Nominé;
Opis vira z dne 13. 3. 2026;
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| Publication date in DiRROS: | 30.04.2026 |
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| Views: | 39 |
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| Downloads: | 24 |
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