Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Application of Fourier Transform infrared spectroscopy (FTIR) coupled with multivariate regression for calcium carbonate (CaCO3) quantification in cement
Graphical abstract Display Omitted
Highlights The carbonation process of cement with supercritical CO2 was reevaluated. Fast, low-cost, and reliable models were obtained to quantify CaCO3 in cement by FTIR. The effect of CO2 on the cement matrix must be considered for the development of PLS. The cement fractions relevant to the PLS regression are portlandite, CaCO3 and C-S-H. The PLS model showed a good correlation coefficient and a low CaCO3 prediction error.
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.
Application of Fourier Transform infrared spectroscopy (FTIR) coupled with multivariate regression for calcium carbonate (CaCO3) quantification in cement
Graphical abstract Display Omitted
Highlights The carbonation process of cement with supercritical CO2 was reevaluated. Fast, low-cost, and reliable models were obtained to quantify CaCO3 in cement by FTIR. The effect of CO2 on the cement matrix must be considered for the development of PLS. The cement fractions relevant to the PLS regression are portlandite, CaCO3 and C-S-H. The PLS model showed a good correlation coefficient and a low CaCO3 prediction error.
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.
Application of Fourier Transform infrared spectroscopy (FTIR) coupled with multivariate regression for calcium carbonate (CaCO3) quantification in cement
Santos, Victor Hugo Jacks Mendes dos (Autor:in) / Pontin, Darlan (Autor:in) / Ponzi, Gabriela Gonçalves Dias (Autor:in) / Stepanha, Amanda Sofia de Guimarães e (Autor:in) / Martel, Renan Bordulis (Autor:in) / Schütz, Marta Kerber (Autor:in) / Einloft, Sandra Mara Oliveira (Autor:in) / Dalla Vecchia, Felipe (Autor:in)
25.10.2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Application of Fourier transform infrared spectroscopy in cement Alkali quantification
| Online Contents | 2014
Application of Fourier transform infrared spectroscopy in cement Alkali quantification
| Online Contents | 2013
Application of Fourier transform infrared spectroscopy in cement Alkali quantification
| Springer Verlag | 2013
Application of Fourier transform infrared spectroscopy in cement Alkali quantification
| Online Contents | 2013
Application of Fourier transform infrared spectroscopy in cement Alkali quantification
| British Library Online Contents | 2014