QNN/autotrain-data-auto2

该数据集是由AutoTrain为项目auto2自动处理的。数据集的语言为英语（BCP-47代码为en）。数据集的结构包括数据实例和字段，数据实例展示了文本的tokens和对应的tags，字段包括tokens和tags。数据集被分为训练集和验证集，训练集有166个样本，验证集有44个样本。

This dataset was automatically processed by AutoTrain for the project auto2. The language of the dataset is English, with its BCP-47 code being en. The dataset structure consists of data instances and fields, where the data instances present the text tokens and their corresponding tags, and the fields include tokens and tags. The dataset is split into a training set and a validation set, with 166 samples in the training set and 44 samples in the validation set.

原始信息汇总

AutoTrain Dataset for project: auto2

数据集描述

该数据集由AutoTrain自动处理，用于项目auto2。

语言

数据集的语言为英语（BCP-47代码：en）。

数据集结构

数据实例

数据集的一个样本如下所示：

json [ { "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_<i>x</i>)", "have", "been", "proposed", "to", "boost", "HER", "performances.", "However,", "the", "stability", "issues,", "e.g.,", "the", "dissolution", "in", "Pd-M", "and", "the", "hydrogen", "releasing", "in", "PdH_<i>x</i>,", "restrict", "the", "industrial", "application", "of", "Pd-based", "HER", "catalysts.", "We", "here", "design", "and", "synthesize", "a", "stable", "Pd-Cu", "hydride", "(", "PdCu_0.2H_0.43", ")", "catalyst,", "combining", "the", "advantages", "of", "both", "Pd-M", "and", "PdH_<i>x</i>", "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_0.2H_0.43", "catalyst", "exhibits", "a", "small", "overpotential", "of", "28", "mV", "at", "10", "mA/cm²", ",", "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>" ], "tags": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 4, 2, 5, 5, 2, 5, 5, 2, 2, 2, 4, 2, 2, 5, 5, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ] }, { "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", "_<i>x</i>", ")", "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", "_<i>x</i>", "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_x", ")", "catalyst,", "developed", "through", "an", "iteration", "of", "the", "operando", "measurement", "directed", "optimization", "cycle,", "is", "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^-2", "with", "1.5", "V", "applied", "bias", "in", "1", "M", "KOH", "electrolyte", "solution.", "</p>", "<p>" ], "tags": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 2, 5, 5, 5, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ] } ]

数据集字段

数据集包含以下字段（也称为“特征”）：

json { "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)" }

数据集分割

数据集分为训练集和验证集。分割大小如下：

分割名称	样本数量
train	166
valid	44