A recently developed technique of Micro-Spatially Offset Raman Spectroscopy (micro-SORS) extends the applicability of Raman spectroscopy to probing thin, highly diffusely scattering layers such as stratified paint samples, enabling their nondestructive chemical characterization. The technique has a wide applicability across areas such as cultural heritage, polymer research, forensics, and biological fields; however, currently, it suffers from a major unaddressed issue related to its ineffectiveness with highly heterogeneous samples. In this paper, we address this unmet need while demonstrating an effective strategy to probe such samples, involving a mapping on scales substantially larger than the scale of heterogeneity. This approach provides an effective means of obtaining robust and representative micro-SORS datasets from which sample composition can be effectively deduced, even in these extreme scenarios. The approach is compared with a basic point collection approach on two-layer paint systems where different layers-top, bottom, or both-are heterogeneous. The study has particular relevance to cultural heritage, where heterogeneous layers are often encountered with painted stratigraphies.
Investigation of Heterogeneous Painted Systems by Micro-Spatially Offset Raman Spectroscopy
Conti Claudia;Botteon Alessandra;Colombo Chiara;Realini Marco;
2017
Abstract
A recently developed technique of Micro-Spatially Offset Raman Spectroscopy (micro-SORS) extends the applicability of Raman spectroscopy to probing thin, highly diffusely scattering layers such as stratified paint samples, enabling their nondestructive chemical characterization. The technique has a wide applicability across areas such as cultural heritage, polymer research, forensics, and biological fields; however, currently, it suffers from a major unaddressed issue related to its ineffectiveness with highly heterogeneous samples. In this paper, we address this unmet need while demonstrating an effective strategy to probe such samples, involving a mapping on scales substantially larger than the scale of heterogeneity. This approach provides an effective means of obtaining robust and representative micro-SORS datasets from which sample composition can be effectively deduced, even in these extreme scenarios. The approach is compared with a basic point collection approach on two-layer paint systems where different layers-top, bottom, or both-are heterogeneous. The study has particular relevance to cultural heritage, where heterogeneous layers are often encountered with painted stratigraphies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.