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- Title
Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà.
- Authors
Díez‐Pastor, José Francisco; Jorge‐Villar, Susana Esther; Arnaiz‐González, Álvar; García‐Osorio, César Ignacio; Díaz‐Acha, Yael; Campeny, Marc; Bosch, Josep; Melgarejo, Joan Carles
- Abstract
Variscite is an aluminium phosphate mineral widely used as a gemstone in antiquity. Knowledge of the ancient trade in variscite has important implications on the historical appreciation of the commercial and migratory movements of human population. The mining complex of Gavà, which dates from the Neolithic, is one of the oldest underground mine sites in Europe, from where variscite was extracted from several mines and at different depths, providing minerals with different properties and a range of colours. In this work, machine learning algorithms have been used to classify variscite samples from Gavà with regard to the identification of their mine of origin and extraction depth. The final objective of the study was to see if the Raman spectroscopic signatures selected by these algorithms had a key spectral significance related to mineral structure and/or composition and validate the use of these computational procedures as a useful tool for detecting variances in the mineral Raman spectra that could facilitate the assignment of the specimens to each mine.
- Subjects
EUROPE; RAMAN spectroscopy; MACHINE learning; PHOSPHATE minerals; ALUMINUM phosphate; HUMAN mechanics
- Publication
Journal of Raman Spectroscopy, 2020, Vol 51, Issue 9, p1563
- ISSN
0377-0486
- Publication type
Article
- DOI
10.1002/jrs.5509