Dataset construction and data science analysis of physicochemical characterization of ordinary Portland cement

Abstract

Abstract This paper presents a dataset construction and data science analysis from the literature results of physicochemical characterization of ordinary Portland cement (OPC). The physicochemical variables included the percentage by mass of calcium oxide (CaO), silicon dioxide (SiO2), aluminum oxide (Al2O3), iron oxide (Fe2O3), magnesium oxide (MgO), sulfuric oxide (SO3), sodium oxide (Na2O), potassium oxide (K2O), titanium oxide (TiO2), free lime (CaOfree), equivalent alkaline (Na2Oeq), loss on ignition, specific surface, density, water-cement ratio, and compressive strength of cement at 28 days. The searching, collection, and assembly of the dataset aimed to evaluate the information related to those variables through exploratory data analysis, enabling a basic understanding of characterization results of OPCs obtained in publications from different types, sources, years, and countries. The dataset provides a useful source of physicochemical characterization of ordinary cement, and the exploratory data analysis provided an understanding of central, dispersion, and data distribution with statistical metrics of each variable and their pair-wise correlations in the assembled dataset. The constructed dataset and its analysis are a starting point to further data, studies, and artificial intelligence models to provide a broader global view of the production and properties of ordinary Portland cement.

Keywords

• Portland cement
• oxides
• data science
• physicochemical properties
• compressive strength