The new challenge in the investigation of cultural heritage is the possibility to obtain stratigraphical information about the distribution of the different organic and inorganic components without sampling. In this paper recently commercialized analytical set-up, which is able to co-register VNIR, SWIR, and XRF spectral data simultaneously, is exploited in combination with an innovative multivariate and multiblock high-throughput data processing for the analysis of multilayered paintings. The instrument allows to obtain elemental and molecular information from superficial to subsurface layers across the investigated area. The chemometric strategy proved to be highly efficient in data reduction and for the extraction and integration of the most useful information coming from the three different spectroscopies, also filling the gap between data acquisition and data understanding through the combination of principal component analysis (PCA), brushing, correlation diagrams and maps (within and between spectral blocks) on the low-level fused. In particular, correlation diagrams and maps provide useful information for the reconstruction of a stratigraphic structure without the need to take any sample, thanks to the effective account for inter-correlation among data (variables), which is able to effectively characterize the possible combinations of components located in the same depth level. The highly innovative technology and the data processing strategy are applied for the multi-level characterization of a complex painting reproduction as an illustrative pilot study.

Catelli E., Li Z., Sciutto G., Oliveri P., Prati S., Occhipinti M., et al. (2023). Towards the non-destructive analysis of multilayered samples: A novel XRF-VNIR-SWIR hyperspectral imaging system combined with multiblock data processing. ANALYTICA CHIMICA ACTA, 1239, 340710-340718 [10.1016/j.aca.2022.340710].

Towards the non-destructive analysis of multilayered samples: A novel XRF-VNIR-SWIR hyperspectral imaging system combined with multiblock data processing

Catelli E.;Li Z.;Sciutto G.;Oliveri P.;Prati S.;Mazzeo R.
2023

Abstract

The new challenge in the investigation of cultural heritage is the possibility to obtain stratigraphical information about the distribution of the different organic and inorganic components without sampling. In this paper recently commercialized analytical set-up, which is able to co-register VNIR, SWIR, and XRF spectral data simultaneously, is exploited in combination with an innovative multivariate and multiblock high-throughput data processing for the analysis of multilayered paintings. The instrument allows to obtain elemental and molecular information from superficial to subsurface layers across the investigated area. The chemometric strategy proved to be highly efficient in data reduction and for the extraction and integration of the most useful information coming from the three different spectroscopies, also filling the gap between data acquisition and data understanding through the combination of principal component analysis (PCA), brushing, correlation diagrams and maps (within and between spectral blocks) on the low-level fused. In particular, correlation diagrams and maps provide useful information for the reconstruction of a stratigraphic structure without the need to take any sample, thanks to the effective account for inter-correlation among data (variables), which is able to effectively characterize the possible combinations of components located in the same depth level. The highly innovative technology and the data processing strategy are applied for the multi-level characterization of a complex painting reproduction as an illustrative pilot study.
2023
Catelli E., Li Z., Sciutto G., Oliveri P., Prati S., Occhipinti M., et al. (2023). Towards the non-destructive analysis of multilayered samples: A novel XRF-VNIR-SWIR hyperspectral imaging system combined with multiblock data processing. ANALYTICA CHIMICA ACTA, 1239, 340710-340718 [10.1016/j.aca.2022.340710].
Catelli E.; Li Z.; Sciutto G.; Oliveri P.; Prati S.; Occhipinti M.; Tocchio A.; Alberti R.; Frizzi T.; Malegori C.; Mazzeo R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/915776
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