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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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# Machine Learning Design of Perovskite Catalytic Properties |
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Dataset containing 2844 perovskite stability data points from DFT |
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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/xcye-zy28](https://doi.org/10.18126/xcye-zy28) |
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- **Year**: 2023 |
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- **Authors**: Jacobs, Ryan, Liu, Jian, Abernathy, Harry, Morgan, Dane |
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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 with sites | | |
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| composition (no brackets) | input | Material composition | | |
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| O pband (eV) | input | DFT-calculated O p-band center | eV | |
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| energy | input | DFT-calculated total energy | eV/cell | |
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| Nominal d # | input | Number of transition metal d electrons | | |
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| Band gap (eV) | input | DFT-calculated band gap | eV | |
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| E_hull (meV/atom) | target | Energy above hull at UHV, 1200 K | meV/atom | |
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| E_above_hull_closed (meV/atom) | target | Energy above hull of closed system | meV/atom | |
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| E_above_hull_open (meV/atom) | target | Energy above hull of open system at 500 C, room ai | meV/atom | |
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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/xcye-zy28") |
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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_perovskite_stability_updated") |
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``` |
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## Citation |
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```bibtex |
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@misc{https://doi.org/10.18126/xcye-zy28 |
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doi = {10.18126/xcye-zy28} |
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url = {https://doi.org/10.18126/xcye-zy28} |
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author = {Jacobs, Ryan and Liu, Jian and Abernathy, Harry and Morgan, Dane} |
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title = {Machine Learning Design of Perovskite Catalytic Properties} |
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keywords = {machine learning, foundry} |
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publisher = {Materials Data Facility} |
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year = {root=2023}} |
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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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