metadata
task_categories:
- token-classification
AutoTrain Dataset for project: pubmed
Dataset Description
This dataset has been automatically processed by AutoTrain for project pubmed.
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",
"been",
"regarded",
"as",
"one",
"of",
"the",
"alternatives",
"to",
"Pt",
"as",
"a",
"promising",
"hydrogen",
"evolution",
"reaction",
"(HER)",
"catalyst.",
"Strategies",
"including",
"Pd-metal",
"alloys",
"(Pd-M)",
"and",
"Pd",
"hydrides",
"(PdH<sub><i>x</i></sub>)",
"have",
"been",
"proposed",
"to",
"boost",
"HER",
"performances.",
"However,",
"the",
"stability",
"issues,",
"e.g.,",
"the",
"dissolution",
"in",
"Pd-M",
"and",
"the",
"hydrogen",
"releasing",
"in",
"PdH<sub><i>x</i></sub>,",
"restrict",
"the",
"industrial",
"application",
"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>",
")",
"catalyst,",
"combining",
"the",
"advantages",
"of",
"both",
"Pd-M",
"and",
"PdH<sub><i>x</i></sub>",
"structures",
"and",
"improving",
"the",
"HER",
"durability",
"simultaneously.",
"The",
"hydrogen",
"intercalation",
"is",
"realized",
"under",
"atmospheric",
"pressure",
"(1.0",
"atm)",
"following",
"our",
"synthetic",
"approach",
"that",
"imparts",
"high",
"stability",
"to",
"the",
"Pd-Cu",
"hydride",
"structure.",
"The",
"obtained",
"PdCu<sub>0.2</sub>H<sub>0.43</sub>",
"catalyst",
"exhibits",
"a",
"small",
"overpotential",
"of",
"28",
"mV",
"at",
"10",
"mA/cm<sup>2</sup>",
",",
"a",
"low",
"Tafel",
"slope",
"of",
"23",
"mV/dec",
",",
"and",
"excellent",
"HER",
"durability",
"due",
"to",
"its",
"appropriate",
"hydrogen",
"adsorption",
"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>",
")",
"bifunctional",
"catalyst.",
"The",
"research",
"was",
"driven",
"by",
"integrated",
"electrochemical",
"analysis,",
"Raman",
"spectroscopy",
"and",
"gravimetric",
"measurements",
"utilizing",
"a",
"novel",
"quartz",
"crystal",
"microbalance",
"spectroelectrochemical",
"cell",
"to",
"uncover",
"the",
"catalytically",
"active",
"species",
"of",
"amorphous",
"CoP",
"<sub><i>x</i></sub>",
"and",
"subsequently",
"modify",
"the",
"material",
"to",
"enhance",
"the",
"activity",
"of",
"the",
"elucidated",
"catalytic",
"phases.",
"Illustrating",
"the",
"power",
"of",
"our",
"approach,",
"the",
"second",
"generation",
"cobalt-iron",
"phosphide",
"(",
"CoFeP<sub>x</sub>",
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"catalyst,",
"developed",
"through",
"an",
"iteration",
"of",
"the",
"operando",
"measurement",
"directed",
"optimization",
"cycle,",
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"superior",
"in",
"both",
"hydrogen",
"and",
"oxygen",
"evolution",
"reactivity",
"over",
"the",
"previous",
"material",
"and",
"is",
"capable",
"of",
"overall",
"water",
"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 |