Benefits of Chemometric and Raman Spectroscopy Applied to the Kinetics of Setting and Early Age Hydration of Cement Paste

Appl Spectrosc. 2023 Jan;77(1):37-52. doi: 10.1177/00037028221135065. Epub 2022 Nov 7.

Abstract

The addition of water is used to past by internal post-curing of hardening cement. Hydration and curing of cementitious are widely identified by non-destructive 1H nuclear magnetic resonance (NMR) measurements of transverse relaxation time and self-diffusion. However, those non-destructive analytical methodologies do not give a truly chemical characterization of the cement matrix during the hydration and curing process. Indeed, the NMR studies only the water dynamics of hydrating cement with internal post-curing. Recent research indicated chemometrics coupled with Raman spectroscopy allows for a better understanding of chemical processes. Recent advances in computing gave industries and research centers the opportunity to generate cost effective data. In this work, an original method is presented, which uses both a data analysis and a non-invasive, non-destructive Raman monitoring of the hydration reaction of a Portland cement. Data was then analyzed by means of chemometrics methods (principal components analysis (PCA), independent components analysis (ICA), and multivariate curve resolution-alternated least-squares (MCR-ALS) with SIMPLe-to-use Interactive Self-modelling Mixture Analysi (SIMPLISMA) and Orthogonal Projection Approach (OP initialization). Results were compared to the ones obtained with thermogravimetric analysis of this cement paste. Besides the consistency of results from both analytical measurements, chemometrics coupled to Raman spectroscopy accurately revealed the details of the setting without any samples collection. The acquisition frequency allowed a proper identification of the occurrence of each of the various phases involved in the hydration and setting process.

Keywords: Chemometrics; ICA; MCR-ALS; PCA; Raman; cement; hydration; independent components analysis; multivariate curve resolution alternating least squares; multivariate resolution; principal component analysis.