SEM-EDS MICROANALYSIS OF ULTRATHIN GLASS AND METAL FRAGMENTS: MEASUREMENT STRATEGY BY MONTE CARLO SIMULATION IN CULTURAL HERITAGE AND ARCHAEOLOGY

• Published in: International journal of conservation science 2020, Vol.11, p.223-232
• Main Authors: Moro, Daniele, Ulian, Gianfranco, Valdre, Giovanni
• Format: Article
• Language: English
• Subjects: Archaeology; Case studies; Chemical composition; Cultural heritage; Cultural resources; Energy; Errors; Fragments; Gold base alloys; Monte Carlo simulation; Morphology; Physics; Scanning electron microscopy; Scientific imaging; Sensors; Shape effects; Simulation; Spatial analysis; Spatial discrimination; Spatial resolution; Spectrometry; Thickness
• ISSN: 2067-533X; 2067-8223

Scanning electron microscopy (SEJM) combined with energy dispersive X-ray spectrometry (EDS) has a very wide range of applications in cultural heritage and archaeology, because of the capability to provide morphological analysis with high spatial resolution, combined with chemical information at the microscale. However, when the size of the materials analyzed approaches the micro- and submicrometre scale, as often found in cultural heritage and archaeology investigations, several effects related to electron and X-ray generation and transport had to be considered to avoid quantification errors. In this work, Monte Carlo simulations are presented for the study of the effects of thickness and shape on quantitative microanalysis by SEM-EDS of ultrathin glass and metal alloys fragments, as usually found in cultural heritage and archaeology. Glass fragments with different chemical composition, elongated shapes, square section and thicknesses from 0.1 to 10 pm, and micro/nanoscale gold alloy fragments were simulated in realistic experimental conditions. The simulations showed an important contribution from the fragments thickness and shape on the X-ray intensity measured by EDS, which in turn affect the quantitification procedure. The results of this study are of general meaning and application, and can be used to develop the most appropriate specific measurement strategy and avoid analytical errors and misinterpretations.