J Build Eng 105055 2022

Numerical and image data from a 2022 study on steel corrosion inhibition. The dataset includes electrochemical measurements, X-ray photoelectron spectroscopy (XPS), Fourier-transform infrared spectroscopy (FTIR) data, and scanning electron microscopy (SEM) images with energy-dispersive X-ray spectroscopy (EDS) analysis. It was authored by Francisco J. Velasco and harvested from the e-cienciaDatos Dataverse repository.

Use Cases

• Training models to predict corrosion inhibitor effectiveness based on electrochemical measurement data.
• Analyzing surface chemical composition changes using XPS and FTIR data mentioned in the description.
• Classifying or segmenting surface morphology features from the provided SEM images.
• Correlating inhibitor molecular properties (from DFT analysis) with experimental performance metrics.

Strengths

• Includes multiple complementary data types: numerical electrochemical data, spectroscopic data (XPS, FTIR), and image data (SEM).
• Data is directly linked to a published 2022 paper, providing a research context.
• Surface analysis (EDS) is performed on steel samples after specific immersion tests, providing targeted experimental results.

Limitations

• Description metadata is limited; actual data quality, file formats, and structure require manual inspection after download.
• Row count, file size, and column-level documentation are absent, which may limit suitability assessment.
• License information is unknown, which could restrict usage.

Provenance

Source

e-cienciaDatos Harvested Dataverse

Collection Method

Data obtained from direct electrochemical measurements, surface spectroscopy (XPS, FTIR), and microscopy (SEM/EDS) as explained in the associated paper.

Time Range

2022

Freshness

Last updated 2024-05-05 07:23:13; freshness should be verified.

Geography

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