Improved chemometric approach for XRF data treatment: application to the reverse glass paintings from the Lipari collection. Issue 7 (2nd February 2023)
- Record Type:
- Journal Article
- Title:
- Improved chemometric approach for XRF data treatment: application to the reverse glass paintings from the Lipari collection. Issue 7 (2nd February 2023)
- Main Title:
- Improved chemometric approach for XRF data treatment: application to the reverse glass paintings from the Lipari collection
- Authors:
- Armetta, Francesco
Saladino, Maria Luisa
Martinelli, Maria Clara
Vilardo, Rosario
Anastasio, Gianfranco
Trusso, Sebastiano
Nardo, Viviana Mollica
Giuffrida, Dario
Ponterio, Rosina Celeste - Abstract:
- Abstract : XRF data of a glass collection from Lipari Museum were processed by multivariate analysis by means of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). Abstract : The Aeolian cultural heritage preserves hundreds of testimonies of the past that have passed through six millennia of history. Among these, the Archeological Park of the Aeolian Islands with the Museum Luigi Bernabò Brea (Italy) preserves a valuable set of artworks, which are related to a little-known 'popular' figurative heritage. It is an assemblage of small glass foils decorated using the technique of reverse painting, datable to between the end of the 17 th century and the end of the 18 th century, and actually under investigation by historians. Here, an X-ray fluorescence (XRF) spectroscopy study (performed with portable equipment) is combined with a multivariate approach that allows us to define the best way to process the data to detect compositional differences and similarities among the glass supports. The Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were applied both on normalized spectra and on normalized peak areas in order to establish the chemometric approach with the highest grouping ability. Results showed that the analysis of the normalized area provides the most reliable grouping based on the different elemental compositions, without problems coming from the background or peak-shape distortions. The obtained results can be used byAbstract : XRF data of a glass collection from Lipari Museum were processed by multivariate analysis by means of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). Abstract : The Aeolian cultural heritage preserves hundreds of testimonies of the past that have passed through six millennia of history. Among these, the Archeological Park of the Aeolian Islands with the Museum Luigi Bernabò Brea (Italy) preserves a valuable set of artworks, which are related to a little-known 'popular' figurative heritage. It is an assemblage of small glass foils decorated using the technique of reverse painting, datable to between the end of the 17 th century and the end of the 18 th century, and actually under investigation by historians. Here, an X-ray fluorescence (XRF) spectroscopy study (performed with portable equipment) is combined with a multivariate approach that allows us to define the best way to process the data to detect compositional differences and similarities among the glass supports. The Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were applied both on normalized spectra and on normalized peak areas in order to establish the chemometric approach with the highest grouping ability. Results showed that the analysis of the normalized area provides the most reliable grouping based on the different elemental compositions, without problems coming from the background or peak-shape distortions. The obtained results can be used by researchers involved in the analysis of XRF data as a guideline to perform chemometrics. Furthermore, regarding the reverse glass, they can be divided into different typologies based on composition differences, providing a further discrimination criterion for historians involved in the study of the collection to determine the provenance and dating of the items. … (more)
- Is Part Of:
- RSC advances. Volume 13:Issue 7(2023)
- Journal:
- RSC advances
- Issue:
- Volume 13:Issue 7(2023)
- Issue Display:
- Volume 13, Issue 7 (2023)
- Year:
- 2023
- Volume:
- 13
- Issue:
- 7
- Issue Sort Value:
- 2023-0013-0007-0000
- Page Start:
- 4495
- Page End:
- 4503
- Publication Date:
- 2023-02-02
- Subjects:
- Chemistry -- Periodicals
540.5 - Journal URLs:
- http://pubs.rsc.org/en/Journals/JournalIssues/RA ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/d2ra08178d ↗
- Languages:
- English
- ISSNs:
- 2046-2069
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8036.750300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 25701.xml