metadata
license: other
task_categories:
- tabular-regression
- tabular-classification
tags:
- materials-science
- chemistry
- foundry-ml
- scientific-data
size_categories:
- 1K<n<10K
Prediction of mechanical properties of biomedical magnesium alloys based on ensemble machine learning
Dataset containing mechanical properties of 365 Mg alloys
Dataset Information
- Source: Foundry-ML
- DOI: 10.18126/myj4-0h48
- Year: 2023
- Authors: Hou, Haobing, Wang, Jianfeng, Ye, Li, Zhu, Shijie, Wang, Liguo, Guan, Shaokang
- Data Type: tabular
Fields
| Field | Role | Description | Units |
|---|---|---|---|
| Mg(wt.%) | input | Amount of Mg | wt% |
| Zn(wt.%) | input | Amount of Zn | wt% |
| Y(wt.%) | input | Amount of Y | wt% |
| Zr(wt.%) | input | Amount of Zr | wt% |
| Nd(wt.%) | input | Amount of Nd | wt% |
| Gd(wt.%) | input | Amount of Gd | wt% |
| solution temperature(°Ê) | input | Solution temperature | degC |
| solution time(h) | input | Solution time | hours |
| homogenization temperature(°Ê) | input | Homogenization temperature | degC |
| homogenization time(h) | input | Homogenization time | hours |
| extrusion temperature(°Ê) | input | Extrusion temperature | degC |
| extrusion ratio | input | Extrusion ratio | |
| aging temperature(°Ê) | input | Aging temperature | degC |
| aging time(h) | input | Aging time | hours |
| UTS(MPa) | target | Ultimate tensile strength | MPa |
| YS(MPa) | target | Yield strength | MPa |
| EL(%) | target | Elongation |
Splits
- train: train
Usage
With Foundry-ML (recommended for materials science workflows)
from foundry import Foundry
f = Foundry()
dataset = f.get_dataset("10.18126/myj4-0h48")
X, y = dataset.get_as_dict()['train']
With HuggingFace Datasets
from datasets import load_dataset
dataset = load_dataset("Dataset_Mg_alloy")
Citation
@misc{https://doi.org/10.18126/myj4-0h48
doi = {10.18126/myj4-0h48}
url = {https://doi.org/10.18126/myj4-0h48}
author = {Hou, Haobing and Wang, Jianfeng and Ye, Li and Zhu, Shijie and Wang, Liguo and Guan, Shaokang}
title = {Prediction of mechanical properties of biomedical magnesium alloys based on ensemble machine learning}
keywords = {machine learning, foundry}
publisher = {Materials Data Facility}
year = {root=2023}}
License
other
This dataset was exported from Foundry-ML, a platform for materials science datasets.