Non-invasive spectroscopic approach for the determination of emerald provenance

Emerald is a cyclosilicate belonging to the beryl-group with the general formula Be3Al2Si6O18 and owe its colour to the presence of Cr3+ and V3+ as minor or trace elements (Aurisicchio et al., 2018). Emeralds have always been considered precious gems throughout history, as evidenced by their widespread distribution in antiquity even far from their mines. Given their value, it is essential to establish a non-invasive analytical procedure applicable to emerald provenance studies. Fourier Transform Infrared Spectroscopy (FTIR) has proven to be a useful non-invasive approach (Branca et al., 2020), thanks to the shape and position of vibrational modes associated with the Si-O stretching (main peak ~1200 cm-1 and shoulder at ~1140 cm-1) and the bands associated with the OH stretching mode of water (in the range 3500-3800 cm-1) which can help in the definition of their provenance. Alongside the advantages offered by non-destructive techniques, it is also important to consider their limitations and drawbacks. In many cases, certain emeralds could not be analysed due to the small size of the samples. In other instances, surfaces rich in inclusions made the analysis challenging. Additionally, for this specific analytical technique to yield high-quality external reflection IR spectra, the samples must have perfectly smooth surfaces. The possibility to analyse various gems from major deposits enabled the collection of a comprehensive set of spectroscopic data. Emerald samples from Afghanistan (Pajshir Valley), Egypt (Gebels Sikaït, Zabara), Ethiopia, Nigeria (Jos, Gashala), Pakistan (Swat Valley), and Russia (Urali) were analysed using External Reflectance (ER) FTIR and μ-FTIR in transmission mode. The combined analysis of score scatter plots and loading plots facilitated the identification of significant spectral bands for ER-FTIR (primarily in the 850–1300 cm⁻¹ range) in the analyzed emerald samples, offering insights into fundamental vibrational modes useful for distinguishing among different provenances. The dataset was processed using a statistical approach—Principal Component Analysis (PCA)—which supports the standardization of parameters for effective provenance discrimination. The combined use of non-destructive and non-invasive analytical techniques (fundamental in the field of cultural heritage) and multivariate statistical analysis (PCA) has produced innovative results in a domain where preserving the integrity of analyzed artifacts has to remain a priority. Aurisicchio, C., Conte, A. M., Medeghini, L., Ottolini, L., & De Vito, C. (2018). Major and trace element geochemistry of emerald from several deposits: Implications for genetic models and classification schemes. Ore Geology Reviews, 94, 351-366, https://doi.org/10.1016/j.oregeorev.2018.02.001 Branca, C., Arcovito, A., Cosio, E., Interdonato, M., Sabatino, G., Wanderlingh, U., & D'Angelo, G. (2020). Combining Fourier transform infrared and Raman spectroscopies with Gaussian deconvolution: An improved approach for the characterization of emeralds. Journal of Raman Spectroscopy, 51(4), 693-701, https://doi.org/10.1002/jrs.5810