README.md

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

# Benchmark AFLOW Data Sets for Machine Learning (Thermal conductivity)

Dataset containing 4887 thermal conductivity values

## Dataset Information

- **Source**: [Foundry-ML](https://github.com/MLMI2-CSSI/foundry)
- **DOI**: [10.18126/s4qn-b840](https://doi.org/10.18126/s4qn-b840)
- **Year**: 2020
- **Authors**: Clement, Conrad L., Kauwe, Steven K., Sparks, Taylor D.
- **Data Type**: tabular

### Fields

| Field | Role | Description | Units |
|-------|------|-------------|-------|
| formula | input | Material composition |  |
| target | target | Thermal conductivity | W/m-K |


### 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/s4qn-b840")
X, y = dataset.get_as_dict()['train']
```

### With HuggingFace Datasets

```python
from datasets import load_dataset

dataset = load_dataset("Dataset_thermalcond_aflow")
```

## Citation

```bibtex
@misc{https://doi.org/10.18126/s4qn-b840
doi = {10.18126/s4qn-b840}
url = {https://doi.org/10.18126/s4qn-b840}
author = {Clement, Conrad L. and Kauwe, Steven K. and Sparks, Taylor D.}
title = {Benchmark AFLOW Data Sets for Machine Learning (Thermal conductivity)}
keywords = {machine learning, foundry}
publisher = {Materials Data Facility}
year = {root=2020}}
```

## License

other

---

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