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Data · dataset · 2026

Electrochemical activated NiOOH/NiFeV-LDH@CC for highly efficient oxygen evolution reaction

Listed in ScienceDB

The time scope of this dataset covers the entire experimental period, and all data are obtained in a standard indoor experimental environment with no spatial resolution requirements for remote sensing or geographic data.

Description

The dataset is mainly composed of structured table data with multiple valid experimental records. In the data table, the row labels represent different experimental groups, test samples or experimental serial numbers, while the column labels stand for various experimental detection indicators, including mass, length, temperature, time, concentration, rate, pressure and other performance parameters.

The commonly used measurement units contain g, mm, ℃, min, mol/L, % and other conventional units, and all measurement standards adopt international general standard units. The dataset maintains good overall completeness with extremely few missing data. Only a small number of data vacancies occur in individual experimental groups due to subtle environmental fluctuations and temporary instrument lag during the test.

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The missing data have been marked in the table, and the vacancy proportion is extremely low, which will not affect the overall data analysis and experimental rule summary. The data contain systematic errors and manual operation errors within a reasonable range. The error sources mainly include the precision limitation of instruments, slight fluctuations of temperature and humidity in the experimental environment, differences in sample placement positions and manual reading deviations.

All data errors are within the industry allowable range and have no adverse impact on experimental conclusions and data analysis results. The submitted data files mainly include summary data sheets, original test data sheets and experimental parameter record sheets, which store sorted statistical data, instrument-derived raw data and basic experimental condition parameters respectively. All data files adopt common formats such as XLSX, CSV and TXT without rare special formats.

These files can be directly opened, viewed and edited by general office and data processing software including Office Excel, Notepad and Origin without dedicated professional software. Featuring high compatibility, the files are applicable to subsequent data analysis, plotting and secondary research.

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Chemical engineering 70% · Satellite remote sensing 65% · Tabular 65%
Provenance · 1 source records, 12 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.j00125.0016611 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[modality].local:modality:tabularenrichment · scidb cnkeyword-concept-rules@1.0.0title+description (65%)
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