AutoTrain Dataset for project: token-classification
Dataset Description
This dataset has been automatically processed by AutoTrain for project token-classification.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"tokens": [
"Pd",
"has",
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"the",
"alternatives",
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"Pt",
"as",
"a",
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"hydrogen",
"evolution",
"reaction",
"(HER)",
"catalyst.",
"Strategies",
"including",
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"alloys",
"(Pd-M)",
"and",
"Pd",
"hydrides",
"(PdH<sub><i>x</i></sub>)",
"have",
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"the",
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"the",
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"PdH<sub><i>x</i></sub>,",
"restrict",
"the",
"industrial",
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"of",
"Pd-based",
"HER",
"catalysts.",
"We",
"here",
"design",
"and",
"synthesize",
"a",
"stable",
"Pd-Cu",
"hydride",
"(",
"PdCu<sub>0.2</sub>H<sub>0.43</sub>",
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"catalyst,",
"combining",
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"PdH<sub><i>x</i></sub>",
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"The",
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"following",
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"the",
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"hydride",
"structure.",
"The",
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",",
"a",
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",",
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"excellent",
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"its",
"appropriate",
"hydrogen",
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"free",
"energy",
"and",
"alleviated",
"metal",
"dissolution",
"rate.",
"</p>",
"<p>"
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{
"tokens": [
"A",
"critical",
"challenge",
"in",
"energy",
"research",
"is",
"the",
"development",
"of",
"earth",
"abundant",
"and",
"cost-effective",
"materials",
"that",
"catalyze",
"the",
"electrochemical",
"splitting",
"of",
"water",
"into",
"hydrogen",
"and",
"oxygen",
"at",
"high",
"rates",
"and",
"low",
"overpotentials.",
"Key",
"to",
"addressing",
"this",
"issue",
"lies",
"not",
"only",
"in",
"the",
"synthesis",
"of",
"new",
"materials,",
"but",
"also",
"in",
"the",
"elucidation",
"of",
"their",
"active",
"sites,",
"their",
"structure",
"under",
"operating",
"conditions",
"and",
"ultimately,",
"extraction",
"of",
"the",
"structure-function",
"relationships",
"used",
"to",
"spearhead",
"the",
"next",
"generation",
"of",
"catalyst",
"development.",
"In",
"this",
"work,",
"we",
"present",
"a",
"complete",
"cycle",
"of",
"synthesis,",
"operando",
"characterization,",
"and",
"redesign",
"of",
"an",
"amorphous",
"cobalt",
"phosphide",
"(",
"CoP",
"<sub><i>x</i></sub>",
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"bifunctional",
"catalyst.",
"The",
"research",
"was",
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"by",
"integrated",
"electrochemical",
"analysis,",
"Raman",
"spectroscopy",
"and",
"gravimetric",
"measurements",
"utilizing",
"a",
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"quartz",
"crystal",
"microbalance",
"spectroelectrochemical",
"cell",
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"uncover",
"the",
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"active",
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"of",
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"CoP",
"<sub><i>x</i></sub>",
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"modify",
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"the",
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"the",
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"catalytic",
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"Illustrating",
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"our",
"approach,",
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"second",
"generation",
"cobalt-iron",
"phosphide",
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"catalyst,",
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"the",
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"cycle,",
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"oxygen",
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"over",
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"electrolysis",
"at",
"a",
"current",
"density",
"of",
"10",
"mA",
"cm<sup>-2</sup>",
"with",
"1.5",
"V",
"applied",
"bias",
"in",
"1",
"M",
"KOH",
"electrolyte",
"solution.",
"</p>",
"<p>"
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}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"tokens": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"tags": "Sequence(feature=ClassLabel(names=['CATALYST', 'CO-CATALYST', 'O', 'Other', 'PROPERTY_NAME', 'PROPERTY_VALUE'], id=None), length=-1, id=None)"
}
Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
|---|---|
| train | 166 |
| valid | 44 |
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