---
license: other
task_categories:
  - tabular-regression
  - tabular-classification
tags:
  - materials-science
  - chemistry
  - foundry-ml
  - scientific-data
size_categories:
  - 1K<n<10K
---

# Machine-Learning Assisted Screening Proton Conducting Co/Fe based Oxide for the Air Electrode of Protonic Solid Oxide Cell

Dataset containing 795 perovskite H absorption data points

## Dataset Information

- **Source**: [Foundry-ML](https://github.com/MLMI2-CSSI/foundry)
- **DOI**: [10.18126/zgzt-xr34](https://doi.org/10.18126/zgzt-xr34)
- **Year**: 2023
- **Authors**: Wang, Ning, Yuan, Baoyin, Zheng, Fangyuan, Mo, Shanyun, Zhang, Xiaohan, Du, Lei, Xing, Lixin, Meng, Ling, Zhao, Lei, Aoki, Yoshitaka, Tang, Chunmei, Ye, Siyu
- **Data Type**: tabular

### Fields

| Field | Role | Description | Units |
|-------|------|-------------|-------|
| Composition | input | Material composition |  |
| temperature_C | input | Temperature of measurement | degC |
| pH2O | input | H2O partial pressure |  |
| Reference | input | Original data reference |  |
| proton_concentration | target | Concentration of H in material | mole/(formula unit) |


### 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/zgzt-xr34")
X, y = dataset.get_as_dict()['train']
```

### With HuggingFace Datasets

```python
from datasets import load_dataset

dataset = load_dataset("Dataset_perovskite_Habs")
```

## Citation

```bibtex
@misc{https://doi.org/10.18126/zgzt-xr34
doi = {10.18126/zgzt-xr34}
url = {https://doi.org/10.18126/zgzt-xr34}
author = {Wang, Ning and Yuan, Baoyin and Zheng, Fangyuan and Mo, Shanyun and Zhang, Xiaohan and Du, Lei and Xing, Lixin and Meng, Ling and Zhao, Lei and Aoki, Yoshitaka and Tang, Chunmei and Ye, Siyu}
title = {Machine-Learning Assisted Screening Proton Conducting Co/Fe based Oxide for the Air Electrode of Protonic Solid Oxide Cell}
keywords = {machine learning, foundry}
publisher = {Materials Data Facility}
year = {root=2023}}
```

## License

other

---

*This dataset was exported from [Foundry-ML](https://github.com/MLMI2-CSSI/foundry), a platform for materials science datasets.*