Mechanical performance dataset for alloy with applications at low temperatures
Abstract Modern technologies such as liquid fuels (hydrogen, oxygen), superconductivity, and quantum technology require materials to serve at very low temperatures, pushing the bounds of material performance by demanding a combination of strength and toughness to tackle various challenges. Steel all...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05512-9 |
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| _version_ | 1849344157056761856 |
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| author | Haoxuan Tang Zhiyuan Chen Xin Yao Zhiping Xu |
| author_facet | Haoxuan Tang Zhiyuan Chen Xin Yao Zhiping Xu |
| author_sort | Haoxuan Tang |
| collection | DOAJ |
| description | Abstract Modern technologies such as liquid fuels (hydrogen, oxygen), superconductivity, and quantum technology require materials to serve at very low temperatures, pushing the bounds of material performance by demanding a combination of strength and toughness to tackle various challenges. Steel alloys are among the most commonly used materials in cryogenic applications. Meanwhile, aluminum and titanium alloys are increasingly recognized for their potential in aerospace and the transportation sectors. Emerging multi-principal element alloys such as medium-entropy and high-entropy alloys offer superior low-temperature mechanical performance, greatly expanding the space for material design. A comprehensive dataset of these low-temperature metallic alloys has been curated from literature and made available in an open repository to meet the need for validated data sources in research and development. The dataset construction workflow incorporates automated extraction using state-of-the-art machine learning and natural language processing techniques, supplemented by manual inspection and correction to improve data extraction efficiency and ensure dataset quality. The product dataset encompasses key performance parameters such as yield strength, tensile strength, elongation at fracture, and Charpy impact energy. The accompanying metadata, detailing material types, chemical compositions, processing and testing conditions, are provided in a standardized format to promote data-driven research in material screening, design, and discovery. |
| format | Article |
| id | doaj-art-ccbfd3b5da1e4aee969fe1f0f97633de |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-ccbfd3b5da1e4aee969fe1f0f97633de2025-08-20T03:42:44ZengNature PortfolioScientific Data2052-44632025-07-011211810.1038/s41597-025-05512-9Mechanical performance dataset for alloy with applications at low temperaturesHaoxuan Tang0Zhiyuan Chen1Xin Yao2Zhiping Xu3Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua UniversityApplied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua UniversityBeijing Minghui Tianhai Gas Storage and Transportation Equipment Sales Co., LtdApplied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua UniversityAbstract Modern technologies such as liquid fuels (hydrogen, oxygen), superconductivity, and quantum technology require materials to serve at very low temperatures, pushing the bounds of material performance by demanding a combination of strength and toughness to tackle various challenges. Steel alloys are among the most commonly used materials in cryogenic applications. Meanwhile, aluminum and titanium alloys are increasingly recognized for their potential in aerospace and the transportation sectors. Emerging multi-principal element alloys such as medium-entropy and high-entropy alloys offer superior low-temperature mechanical performance, greatly expanding the space for material design. A comprehensive dataset of these low-temperature metallic alloys has been curated from literature and made available in an open repository to meet the need for validated data sources in research and development. The dataset construction workflow incorporates automated extraction using state-of-the-art machine learning and natural language processing techniques, supplemented by manual inspection and correction to improve data extraction efficiency and ensure dataset quality. The product dataset encompasses key performance parameters such as yield strength, tensile strength, elongation at fracture, and Charpy impact energy. The accompanying metadata, detailing material types, chemical compositions, processing and testing conditions, are provided in a standardized format to promote data-driven research in material screening, design, and discovery.https://doi.org/10.1038/s41597-025-05512-9 |
| spellingShingle | Haoxuan Tang Zhiyuan Chen Xin Yao Zhiping Xu Mechanical performance dataset for alloy with applications at low temperatures Scientific Data |
| title | Mechanical performance dataset for alloy with applications at low temperatures |
| title_full | Mechanical performance dataset for alloy with applications at low temperatures |
| title_fullStr | Mechanical performance dataset for alloy with applications at low temperatures |
| title_full_unstemmed | Mechanical performance dataset for alloy with applications at low temperatures |
| title_short | Mechanical performance dataset for alloy with applications at low temperatures |
| title_sort | mechanical performance dataset for alloy with applications at low temperatures |
| url | https://doi.org/10.1038/s41597-025-05512-9 |
| work_keys_str_mv | AT haoxuantang mechanicalperformancedatasetforalloywithapplicationsatlowtemperatures AT zhiyuanchen mechanicalperformancedatasetforalloywithapplicationsatlowtemperatures AT xinyao mechanicalperformancedatasetforalloywithapplicationsatlowtemperatures AT zhipingxu mechanicalperformancedatasetforalloywithapplicationsatlowtemperatures |