RESUMO
Analytical chemistry on archaeological material is an essential part of modern archaeological investigations and from year to year, instrumental improvement has made it possible to generate data at a high spatial and temporal frequency. In particular, Raman spectral imaging can be successfully applied in archaeological research by its simplicity of implementation to study past human societies through the analysis of their material remains. This technique makes it possible to simultaneously obtain spatial and spectral information by preserving sample integrity. However, because of the inherent complexity of the samples in Archaeology (e.g. seniority, fragility, lack or full absence of any information about its composition), chemical interpretation can be difficult at first glance. Indeed, specific problems of spectral selectivity related to unexpected chemical compounds could appear due to their state of conservation. Furthermore, detecting minor compounds becomes challenging as major components impose their contributions in the acquired spectra. Therefore, a relevant chemometric approach has been introduced in this context to characterize distinct spectral sources in a Raman imaging dataset of an archaeological specimen - a mosaic fragment. The fragment was unearthed during the Ruscino archaeological dig on the outskirts of Perpignan, France. It dates back to the oppidum period. The aim is to extract selective spectral information from pixel clustering analysis in order to enhance the initial optimisation step within the Multivariate Curve Resolution and Alternating Least-Squares (MCR-ALS) algorithm, a well-known signal unmixing technique. The underlying principle of the MCR-ALS is that the acquired spectra can be expressed as linear combinations of pure spectra of all individual components present in the chemical system under study. Sometimes it can be difficult to obtain the desired results through the algorithm, particularly if initial estimates of spectral or concentration profiles are inaccurate due to complex signals, noise or lack of selectivity, resulting in rank deficiency (i.e. a poor estimation of the total number of pure signals). For this reason, an innovative threshold-based clustering algorithm, combined with multiple Orthogonal Projection Approaches (OPA), has been developed to improve matrix rank investigation and thus the initialisation step of the MCR-ALS approach before optimisation. The effective analysis of Raman imaging data for an archaeological mosaic played a crucial role in uncovering significant chemical information about a particular biogenic material. This insight sheds light on the origins of mortar manufacture during the oppidum period.
RESUMO
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.
