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---
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.*
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