Datasets:

foundry-ml
/

dataset_debyet_aflow

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 (Debye Temperature)

Dataset containing calculated Debye temperatures of 4896 materials

Dataset Information

Source: Foundry-ML
DOI: 10.18126/33r4-8t58
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	Debye Temperature	K

Splits

train: train

Usage

With Foundry-ML (recommended for materials science workflows)

from foundry import Foundry

f = Foundry()
dataset = f.get_dataset("10.18126/33r4-8t58")
X, y = dataset.get_as_dict()['train']

With HuggingFace Datasets

from datasets import load_dataset

dataset = load_dataset("Dataset_debyeT_aflow")

Citation

@misc{https://doi.org/10.18126/33r4-8t58
doi = {10.18126/33r4-8t58}
url = {https://doi.org/10.18126/33r4-8t58}
author = {Clement, Conrad L. and Kauwe, Steven K. and Sparks, Taylor D.}
title = {Benchmark AFLOW Data Sets for Machine Learning (Debye Temperature)}
keywords = {machine learning, foundry}
publisher = {Materials Data Facility}
year = {root=2020}}

License

other

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