Quantitative characterization of aggregates and their chemical constituents in terms of acid and alkaline indicators
Source abstract
Abstract
The acidity and alkalinity of aggregates greatly affect the stability, demulsification rate, and road performance of asphalt mixtures. To study the effect of acidity and alkalinity and chemical composition of aggregates, five aggregates, namely limestone (S1, S2, S3, S4) and basalt (X), were studied. The pH and alkalinity values of aggregates and their main chemical compositions (MgO, Al2O3, CaO, Fe2O3, and SiO2) were tested. The pH/alkalinity measured values and pH/alkalinity composite values of the aggregates were analyzed using grey correlation and principal component analyses. The findings indicated a strong correlation between the composite and measured values for aggregate acidity and alkalinity indexes (pH: 0.9105, alkalinity: 0.9241). Additionally, the principal component analysis demonstrated that the composite values were in good agreement with the measured values (pH: R2 = 0.746, alkalinity: R2 = 0.992), which corroborated the grey correlation and regression model results, confirming significant correlations. This result indicates that the pH/alkaline index of the chemical constituents of the aggregate can be used to characterize the pH/alkaline index of the aggregate. The relationship model between aggregate and their chemical constituent’s acid and alkaline indexes can provide a theoretical reference for the in-depth study of the application of aggregate acid and alkaline in road engineering.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Asphalt Pavement Performance Evaluation · Infrastructure Maintenance and Monitoring · Concrete and Cement Materials Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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