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--- |
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license: other |
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task_categories: |
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- tabular-regression |
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- tabular-classification |
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tags: |
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- materials-science |
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- chemistry |
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- foundry-ml |
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- scientific-data |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Metallic Glasses and their Properties |
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Dataset containing experimental max casting diameters of 998 metallic glasses |
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## Dataset Information |
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- **Source**: [Foundry-ML](https://github.com/MLMI2-CSSI/foundry) |
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- **DOI**: [10.18126/fs5e-kr15](https://doi.org/10.18126/fs5e-kr15) |
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- **Year**: 2021 |
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- **Authors**: Voyles, Paul M, Schultz, Lane E., Morgan, Dane, Francis, Carter, Afflerbach, Benjamin, Hakeem, Abdulrhman |
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- **Data Type**: tabular |
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### Fields |
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| Field | Role | Description | Units | |
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|-------|------|-------------|-------| |
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| Composition | input | Material composition | | |
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| Reference | input | Original data reference | | |
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| Tg_[K] | input | Glass transition temperature | K | |
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| Tx_[K] | input | Crystallization temperature | K | |
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| Tl_[K] | input | Liquidus temperature | K | |
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| Zmax_[mm] | input | Maximum casting size | mm | |
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| Dmax_[mm] | target | Maximum casting diameter | mm | |
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### Splits |
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- **train**: train |
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## Usage |
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### With Foundry-ML (recommended for materials science workflows) |
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```python |
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from foundry import Foundry |
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f = Foundry() |
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dataset = f.get_dataset("10.18126/fs5e-kr15") |
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X, y = dataset.get_as_dict()['train'] |
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``` |
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### With HuggingFace Datasets |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("Dataset_metallicglass_Dmax") |
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``` |
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## Citation |
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```bibtex |
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@misc{https://doi.org/10.18126/fs5e-kr15 |
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doi = {10.18126/fs5e-kr15} |
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url = {https://doi.org/10.18126/fs5e-kr15} |
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author = {Voyles, Paul M and Schultz, Lane E. and Morgan, Dane and Francis, Carter and Afflerbach, Benjamin and Hakeem, Abdulrhman} |
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title = {Metallic Glasses and their Properties} |
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keywords = {machine learning, foundry} |
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publisher = {Materials Data Facility} |
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year = {root=2021}} |
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``` |
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## License |
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other |
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--- |
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*This dataset was exported from [Foundry-ML](https://github.com/MLMI2-CSSI/foundry), a platform for materials science datasets.* |
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