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Vicker's hardness dataset #786

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Vicker's hardness dataset #786

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16 changes: 16 additions & 0 deletions matminer/datasets/dataset_metadata.json
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Original file line number Diff line number Diff line change
Expand Up @@ -961,5 +961,21 @@
"reference": "https://citrination.com/datasets/150557/",
"url": "https://ndownloader.figshare.com/files/28333845",
"hash": "7d0c9c74fd52995b876bd251a7732b5498314702441fa463197fb492be68ecc0"
},
"zhang_brgoch_load_vickers_hardness": {
"bibtex_refs": [
"@article{Zhang2020,\n doi = {10.1002/adma.202005112},\n url = {https://doi.org/10.1002/adma.202005112},\n year = {2020},\n month = dec,\n publisher = {Wiley},\n volume = {33},\n number = {5},\n pages = {2005112},\n author = {Ziyan Zhang and Aria Mansouri Tehrani and Anton O. Oliynyk and Blake Day and Jakoah Brgoch},\n title = {Finding the Next Superhard Material through Ensemble Learning},\n journal = {Advanced Materials}\n}",
],
"columns":{
"composition": "Chemical formula. One chemical formula may correspond to multiple separate measurements.",
"hardness": "Vicker's load-dependent hardness, in GPa.",
"load": "Applied load, in N."
},
"description": "Dataset of 1061 experimentally measured load-dependent Vicker's hardness measurements. Multiple measurements may correspond to one composition. Collated by Zhang et al.",
"file_type": "json.gz",
"num_entries": 1061,
"reference": "https://doi.org/10.1002/adma.202005112",
"url": null,
"hash": null
}
}