foundry-ml/dataset_perovskite_habs
Machine-Learning Assisted Screening Proton Conducting Co/Fe based Oxide for the Air Electrode of Protonic Solid Oxide Cell Dataset containing 795 perovskite H absorption data points Dataset Information Source: Foundry-ML DOI: 10.18126/zgzt-xr34 Year: 2023 Authors: Wang, Ning, Yuan, Baoyin, Zheng, Fangyuan, Mo, Shanyun, Zhang, Xiaohan, Du, Lei, Xing, Lixin, Meng, Ling, Zhao, Lei, Aoki, Yoshitaka, Tang, Chunmei, Ye, Siyu Data Type: tabular Fields… See the full description on the dataset page: https://huggingface.co/datasets/foundry-ml/dataset_perovskite_habs.
Machine-Learning Assisted Screening Proton Conducting Co/Fe based Oxide for the Air Electrode of Protonic Solid Oxide Cell
Dataset containing 795 perovskite H absorption data points
Dataset Information
- Source: Foundry-ML
- DOI: 10.18126/zgzt-xr34
- Year: 2023
- Authors: Wang, Ning, Yuan, Baoyin, Zheng, Fangyuan, Mo, Shanyun, Zhang, Xiaohan, Du, Lei, Xing, Lixin, Meng, Ling, Zhao, Lei, Aoki, Yoshitaka, Tang, Chunmei, Ye, Siyu
- Data Type: tabular
Fields
Splits
- train: train
Usage
With Foundry-ML (recommended for materials science workflows)
from foundry import Foundry
f = Foundry()
dataset = f.get_dataset("10.18126/zgzt-xr34")
X, y = dataset.get_as_dict()['train']With HuggingFace Datasets
from datasets import load_dataset
dataset = load_dataset("Dataset_perovskite_Habs")Citation
@misc{https://doi.org/10.18126/zgzt-xr34
doi = {10.18126/zgzt-xr34}
url = {https://doi.org/10.18126/zgzt-xr34}
author = {Wang, Ning and Yuan, Baoyin and Zheng, Fangyuan and Mo, Shanyun and Zhang, Xiaohan and Du, Lei and Xing, Lixin and Meng, Ling and Zhao, Lei and Aoki, Yoshitaka and Tang, Chunmei and Ye, Siyu}
title = {Machine-Learning Assisted Screening Proton Conducting Co/Fe based Oxide for the Air Electrode of Protonic Solid Oxide Cell}
keywords = {machine learning, foundry}
publisher = {Materials Data Facility}
year = {root=2023}}License
other
This dataset was exported from [Foundry-ML](https://github.com/MLMI2-CSSI/foundry), a platform for materials science datasets.
