Upload README.md with huggingface_hub

README.md

@@ -1,31 +1,85 @@
 ---
-dataset_info:
-  features:
-  - name: Composition
-    dtype: string
-  - name: Temperature (degC)
-    dtype: float64
-  - name: PO2 (%)
-    dtype: float64
-  - name: PH2O (%)
-    dtype: float64
-  - name: Grainsize
-    dtype: float64
-  - name: Ref
-    dtype: string
-  - name: Carrier Type
-    dtype: string
-  - name: Conductivity (S/cm)
-    dtype: float64
-  splits:
-  - name: train
-    num_bytes: 949477
-    num_examples: 7230
-  download_size: 154236
-  dataset_size: 949477
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: other
+task_categories:
+  - tabular-regression
+  - tabular-classification
+tags:
+  - materials-science
+  - chemistry
+  - foundry-ml
+  - scientific-data
+size_categories:
+  - 1K<n<10K
 ---
+
+# Accelerated design and discovery of perovskites with high conductivity for energy applications through machine learning
+
+Dataset containing 7230 perovskite conductivity data points
+
+## Dataset Information
+
+- **Source**: [Foundry-ML](https://github.com/MLMI2-CSSI/foundry)
+- **DOI**: [10.18126/f1vb-et73](https://doi.org/10.18126/f1vb-et73)
+- **Year**: 2021
+- **Authors**: Priya, Pikee, Aluru, N. R.
+- **Data Type**: tabular
+
+### Fields
+
+| Field | Role | Description | Units |
+|-------|------|-------------|-------|
+| Composition | input | Material composition |  |
+| Temperature (degC) | input | Temperature of measurement | degC |
+| PO2 (%) | input | Oxygen partial pressure |  |
+| PH2O (%) | input | Water partial pressure |  |
+| Grainsize | input | Grain size | microns |
+| Ref | input | Original reference |  |
+| Carrier Type | input | Designation of dominant carrier type |  |
+| Conductivity (S/cm) | target | Total conductivity | S/cm |
+
+
+### Splits
+
+- **train**: train
+
+
+## Usage
+
+### With Foundry-ML (recommended for materials science workflows)
+
+```python
+from foundry import Foundry
+
+f = Foundry()
+dataset = f.get_dataset("10.18126/f1vb-et73")
+X, y = dataset.get_as_dict()['train']
+```
+
+### With HuggingFace Datasets
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Dataset_perovskite_conductivity")
+```
+
+## Citation
+
+```bibtex
+@misc{https://doi.org/10.18126/f1vb-et73
+doi = {10.18126/f1vb-et73}
+url = {https://doi.org/10.18126/f1vb-et73}
+author = {Priya, Pikee and Aluru, N. R.}
+title = {Accelerated design and discovery of perovskites with high conductivity for energy applications through machine learning}
+keywords = {machine learning, foundry}
+publisher = {Materials Data Facility}
+year = {root=2021}}
+```
+
+## License
+
+other
+
+---
+
+*This dataset was exported from [Foundry-ML](https://github.com/MLMI2-CSSI/foundry), a platform for materials science datasets.*