Abstract
Partial least squares (PLS) regression models were developed to quantify CaCO3 in cement and to study the CO2 effect on the material matrix. PLS results presented good correlation coefficient (R2 = 0.9995) and low estimation error (RMSEP = 3.61 mg CaCO3/g cement). From the results, it was observed that the portlandite consumption, the increase in CaCO3 content and the C-S-H decalcification-polymerization are the most relevant cement chemical transformations. Thus, it was concluded that: i) it is possible to obtain fast, low-cost, and reliable models to quantify CaCO3 by FTIR and ii) the method is applicable to study carbonated cement-based materials.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call