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Correlation of Cement Performance Property Measurements with C3S/C2S Ratio Determined by Solid State 29Si NMR Measurements

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journal contribution
posted on 2008-08-06, 00:00 authored by Christopher L. Edwards, Rickey Morgan, Lewis Norman, Gary P. Funkhouser, Andrew R. Barron
The physicochemical and engineering performance properties of several API class G and H ordinary Portland cements (OPCs) from various foreign and domestic sources have been investigated in comparison with the tricalcium silicate/dicalcium silicate ratio (C3S/C2S) as determined by magic angle spinning (MAS) 29Si nuclear magnetic resonance (NMR) experiments. XRF-derived oxide analysis appears to provide a lower C3S/C2S ratio than determined by NMR analysis. Furthermore, oxide analysis suggests that all the cements have a C3S/C2S ratio of 2−5, while our NMR method suggests the actual range is significantly broader. Determination of C3S/C2S ratios by NMR provides an effective method of analysis for cements, owing to NMR’s direct measurement of the minerals in question. NMR C3S/C2S ratios demonstrate predictive ability for the determination of engineering performance properties. This is especially the case for prediction of strength development; in keeping with generally accepted understanding of cement hydration behavior, the strength development correlates with increasing C3S/C2S ratio, i.e., C3S content. The observed correlation between NMR-derived silicate ratio and strength development holds for cements in the presence of either a retarder (lignosulfonate) or a fluid loss additive (N,N-dimethylformamide/2-acrylamido-2-methylpropanesulfonic acid copolymer). No significant correlation is observed between C3S/C2S ratio and the 72 h crush strength. The lack of dependency of either thickening time or Young’s modulus to the C3S/C2S ratio as determined by MAS 29Si NMR measurements suggests that these physical properties are independent of the relative silicate composition. No correlations are observed between any physical property and the silicate ratio derived from XRF data.

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