Abstract
Il progetto di ricerca INSIDE ha l'obiettivo di rivoluzionare il concetto di imaging iperspettrale (HSI) nei domini spettrali del vicino infrarosso (NIR) e della fluorescenza a raggi X (XRF), evolvendo da una tecnica di analisi di superficie a una tomografia spettrale 3D in profondità. A questo scopo, il progetto valuterà profondità di penetrazione dei raggi NIR e X incidenti e sfrutterà, per la prima volta, questa proprietà per ottenere immagini spettrali 3D altamente informative di campioni eterogenei. La ricerca riguarderà tre principali campi di applicazione: analisi degli alimenti, scienza della conservazione e scienze forensi. I fattori chiave che influenzano la profondità di penetrazione dei raggi NIR e X, così come le loro interazioni, verranno studiati mediante l'applicazione di design di esperimenti multivariati (MDOE). Strategie di separazione multivariata, tra cui la multivariate curve resolution (MCR) e algoritmi di super-risoluzione, saranno applicate per ottenere informazioni chimiche 3D dai dati iperspettrali in modo efficiente. Verranno inoltre sviluppati strumenti adatti per la visualizzazione grafica 3D per la conversione delle informazioni iperspettrali NIR e XRF deconvolute in mappe chimiche 3D.
Results achieved
The INSIDE project successfully achieved its main objective of advancing hyperspectral imaging (HSI) beyond conventional surface analysis towards a non-invasive analytical approach capable of providing three-dimensional chemical information from heterogeneous materials. By integrating near-infrared (NIR) hyperspectral imaging, X-ray fluorescence (XRF) hyperspectral imaging, advanced chemometric data processing, multiblock data fusion and confirmatory analytical techniques, the project delivered a robust and validated methodological framework for in-depth chemical mapping applicable to several research fields. A major scientific achievement was the comprehensive investigation of the factors governing the penetration depth of NIR and XRF radiation. Through multivariate design of experiments (MDOE), representative reference materials specifically designed by the project partners, and the systematic optimization of instrumental and sample-related parameters, INSIDE established the scientific basis for exploiting subsurface information in a controlled and reproducible manner. These studies demonstrated that penetration depth can be tuned according to both instrumental settings and sample properties, enabling the acquisition of chemically meaningful information from different depths within heterogeneous materials. Preliminary evaluation have been also reported in review published by all the units "Exploiting the penetration depth of XRF and NIR radiation: from 2D to 3D spectral imaging" (TrAC – Trends in Analytical Chemistry, 2026). The project also resulted in the development of innovative analytical protocols for 3D NIR and 3D XRF hyperspectral mapping. Dedicated chemometric workflows, including multivariate curve resolution, multiblock analysis, spectral unmixing, deep-learning strategies and data fusion approaches, were implemented to extract reliable three-dimensional chemical information from complex hyperspectral datasets. In parallel, dedicated software tools and representative reference sample sets were developed to support method optimization, validation and reproducibility. The project also introduced novel strategies for multimodal spectral image fusion and data-driven enhancement of spectroscopic data, as demonstrated by publications in Analytical Chemistry ("What lies INSIDE: chemometric insights on the penetration depth of near infrared radiation in spectral imaging configurations) and ACS Measurement Science Au (Expanding the Capabilities of Portable Mapping in Macroscopic External Reflection FT-IR through a Targeted Data-Driven Spectral Enhancement and Denoising Strategy). An important outcome of the project was the successful integration of complementary hyperspectral modalities. In particular, the co-registration of VIS-NIR-SWIR reflectance imaging and XRF imaging, combined with multiblock chemometric approaches, enabled a comprehensive characterization of complex stratified systems by simultaneously exploiting molecular and elemental information. This integrated workflow significantly improved the interpretation of multilayered samples compared with the use of individual analytical techniques. The developed methodologies were successfully validated in three strategic application areas. In cultural heritage, the project enabled the non-invasive investigation of multilayered paintings, painted mock-ups and bioarchaeological materials, providing valuable information on hidden stratigraphic features and material distribution. In food science, the developed approaches allowed the investigation of biochemical processes occurring beneath the surface of heterogeneous food matrices and demonstrated the feasibility of quality assessment through packaging. In forensic science, the methodologies were successfully applied to the characterization of biological fluids deposited on textiles and automotive paint fragments, with the results systematically confirmed by complementary microscopic and separation-based analytical techniques. Several application-oriented studies published during the project, including contributions in Talanta, Microchemical Journal, Journal of Analysis and Testing, and Analytical Chemistry, demonstrate the versatility of the proposed analytical framework across different application domains. The project generated significant scientific and technological outputs. To date, seven Gold Open Access papers have been published in high-impact international journals, with additional manuscripts currently under review or in preparation. The results have been disseminated through invited lectures, international conferences, specialized training schools and workshops, while FAIR-compliant repositories have been established through Zenodo and GitHub to ensure the accessibility and long-term reuse of research outputs.Project details
Unibo Team Leader: Giorgia Sciutto
Unibo involved Department/s:
Dipartimento di Chimica "Giacomo Ciamician"
Coordinator:
Università degli Studi di GENOVA(Italy)
Total Unibo Contribution: Euro (EUR) 66.772,00
Project Duration in months: 24
Start Date:
28/09/2023
End Date:
28/02/2026
