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Mechanical performance dataset for alloy with applications at low temperatures
Haoxuan Tang1, Zhiyuan Chen1, Xin Yao2
1Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing, 100084, China.
Scientific Data
|July 15, 2025
Summary
A new dataset of metallic alloys for cryogenic applications was created using machine learning. This resource supports research and development in advanced materials for extreme low-temperature environments.
Area of Science:
- Materials Science
- Mechanical Engineering
- Low-Temperature Physics
Background:
- Advanced technologies like liquid fuels, superconductivity, and quantum technology necessitate materials with exceptional strength and toughness at cryogenic temperatures.
- Steel, aluminum, and titanium alloys are commonly used, but emerging medium- and high-entropy alloys show superior low-temperature mechanical properties.
- A need exists for validated data sources to accelerate research and development in these demanding applications.
Purpose of the Study:
- To curate and provide a comprehensive, open-access dataset of metallic alloys for cryogenic applications.
- To facilitate data-driven research in material screening, design, and discovery for low-temperature environments.
- To establish a standardized format for material properties and metadata.
Main Methods:
- Automated data extraction from literature using machine learning and natural language processing.
- Supplementation of automated extraction with manual inspection and correction for enhanced data quality.
- Curation of key performance parameters (yield strength, tensile strength, elongation, impact energy) and metadata (composition, processing, testing conditions).
Main Results:
- A comprehensive dataset of low-temperature metallic alloys has been successfully curated and made publicly available.
- The dataset includes critical mechanical properties and detailed metadata in a standardized format.
- The data extraction workflow demonstrated high efficiency and quality through a combination of automated and manual processes.
Conclusions:
- The curated dataset provides a valuable resource for researchers and developers working with materials at cryogenic temperatures.
- This open repository will accelerate the discovery and design of novel alloys for demanding technological applications.
- The standardized data format promotes reproducibility and facilitates collaborative research in materials science.
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