Young Modulus Metals Dataset
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Young Modulus Metals Dataset
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Young Modulus Metals Dataset
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Young Modulus Metals Dataset
Use Case
Young Modulus Metals Dataset
Description
Access a comprehensive dataset of Young’s Modulus values for 50 metals, ranging from 1.7 GPa to 447 GPa.
Description:
This dataset features the Young’s Modulus values (measured in GPa) for 50 different metals, spanning categories like alkali metals, alkaline earth metals, transition metals, and rare earth elements. Young’s Modulus is a critical mechanical property that quantifies a material’s stiffness when subjected to tensile or compressive stress. This dataset is a valuable resource for materials science, mechanical engineering, and physics research.
Key Highlights
- Data Scope: Covers 50 metals with chemical symbols and corresponding Young’s Modulus values.
- Range of Stiffness: Includes soft metals like cesium (1.7 GPa) and extremely stiff metals like ruthenium (447 GPa).
- Data Integrity: Features clean, complete, and verified data with no missing or duplicate entries.
Applications in Data Science & Engineering
This dataset serves as a foundation for a range of innovative applications in engineering, education, and data science:
- Predictive Modeling: Train machine learning models to estimate mechanical properties using elemental features like atomic weight or density.
- Cluster Analysis: Group metals into clusters based on mechanical properties or periodic trends.
- Correlation Studies: Analyze relationships between Young’s Modulus and other physical/chemical attributes like atomic radius, density, or melting point.
- Engineering Simulations: Leverage the dataset in finite element analysis (FEA) and material selection processes.
- Educational Visualizations: Create engaging graphs or infographics to illustrate material property trends across the periodic table.
Dataset Overview
- Metals Included: 50 unique metals with their chemical symbols.
- Young’s Modulus Values: From 1.7 GPa (Cesium) to 447 GPa (Ruthenium).
- Data Quality:
- Verified for accuracy using authoritative scientific references.
- Ensures 100% completeness with no missing values.
- Free from duplicate entries.
Ethical and Reliable Data
The dataset has been compiled using publicly available scientific data, ensuring ethical sourcing and adherence to open-data standards. Verification was performed through cross-referencing with peer-reviewed academic resources.
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