For investigating and modeling the swelling potential of anhydrite rocks, it is important to define a fast but accurate, reliable, and repeatable procedure for mineral identification and quantification of anhydrite mineral in rock samples. We propose a quantitative evaluation of the applicability of two different SEM-based approaches (namely, image analysis and the use of the O/S atomic ratio) for the identification and quantification of anhydrite in polished slices of rock. We compare the results obtained with the bulk densities of the samples and with the outcomes of thermogravimetric analyses, demonstrating high convergence between the different data. We eventually propose a critical comparison between the proposed approaches and the existing methods, overall providing a practical guide for the selection of the best analytical procedure for the quantification of anhydrite content in rocks and, consequently, for the correct estimation of swelling potential.

SEM-Based Approaches for the Identification and Quantification of Anhydrite

Paschetto, Arianna;Costa, Emanuele;Bonetto, S. M. R.;Mosca, Pietro;Caselle, Chiara
2025-01-01

Abstract

For investigating and modeling the swelling potential of anhydrite rocks, it is important to define a fast but accurate, reliable, and repeatable procedure for mineral identification and quantification of anhydrite mineral in rock samples. We propose a quantitative evaluation of the applicability of two different SEM-based approaches (namely, image analysis and the use of the O/S atomic ratio) for the identification and quantification of anhydrite in polished slices of rock. We compare the results obtained with the bulk densities of the samples and with the outcomes of thermogravimetric analyses, demonstrating high convergence between the different data. We eventually propose a critical comparison between the proposed approaches and the existing methods, overall providing a practical guide for the selection of the best analytical procedure for the quantification of anhydrite content in rocks and, consequently, for the correct estimation of swelling potential.
2025
15
17
1
14
image analysis; image segmentation; mineralogical characterization; Scanner Electron Microscope; swelling of anhydrite
Giordano, Emmanuele; Paschetto, Arianna; Costa, Emanuele; Bonetto, S. M. R.; Mosca, Pietro; Frasca, Gianluca; Caselle, Chiara
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2095170
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