foundry-ml/dataset_perovskite_formatione

Computational screening of perovskite metal oxides for optimal solar light capture

Dataset containing 9646 perovskite formation energy data points

Dataset Information

• Source: Foundry-ML
• DOI: 10.18126/xmh8-d711
• Year: 2011
• Authors: Castelli, Ivano E., Olsen, Thomas, Datta, Soumendu, Landis, David D., Dahl, Søren, Thygesena, Kristian S., Jacobsen, Karsten W.
• Data Type: tabular

Fields

Field	Role	Description	Units
formula	input	Material composition
target	target	Formation energy	eV/atom

Splits

• train: train

Usage

With Foundry-ML (recommended for materials science workflows)

from foundry import Foundry

f = Foundry()
dataset = f.get_dataset("10.18126/xmh8-d711")
X, y = dataset.get_as_dict()['train']

With HuggingFace Datasets

from datasets import load_dataset

dataset = load_dataset("Dataset_perovskite_formationE")

Citation

@misc{https://doi.org/10.18126/xmh8-d711
doi = {10.18126/xmh8-d711}
url = {https://doi.org/10.18126/xmh8-d711}
author = {Castelli, Ivano E. and Olsen, Thomas and Datta, Soumendu and Landis, David D. and Dahl, Søren and Thygesena, Kristian S. and Jacobsen, Karsten W.}
title = {Computational screening of perovskite metal oxides for optimal solar light capture}
keywords = {machine learning, foundry}
publisher = {Materials Data Facility}
year = {root=2011}}

License

other

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