foundry-ml/dataset_thermalexp_aflow

Benchmark AFLOW Data Sets for Machine Learning (Thermal expansion)

Dataset containing 4886 thermal expansion coefficients

Dataset Information

• Source: Foundry-ML
• DOI: 10.18126/qmrs-jg02
• 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 expansion coefficient	K^-1

Splits

• train: train

Usage

With Foundry-ML (recommended for materials science workflows)

from foundry import Foundry

f = Foundry()
dataset = f.get_dataset("10.18126/qmrs-jg02")
X, y = dataset.get_as_dict()['train']

With HuggingFace Datasets

from datasets import load_dataset

dataset = load_dataset("Dataset_thermalexp_aflow")

Citation

@misc{https://doi.org/10.18126/qmrs-jg02
doi = {10.18126/qmrs-jg02}
url = {https://doi.org/10.18126/qmrs-jg02}
author = {Clement, Conrad L. and Kauwe, Steven K. and Sparks, Taylor D.}
title = {Benchmark AFLOW Data Sets for Machine Learning (Thermal expansion)}
keywords = {machine learning, foundry}
publisher = {Materials Data Facility}
year = {root=2020}}

License

other

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This dataset was exported from Foundry-ML, a platform for materials science datasets.