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Data Processing: A Closer Look at Cultural Heritage Material

Grant number: 23/07377-4
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Start date: August 01, 2023
End date: July 31, 2025
Field of knowledge:Physical Sciences and Mathematics - Physics - Nuclear Physics
Principal Investigator:Márcia de Almeida Rizzutto
Grantee:Maria Clara de Oliveira Flores
Host Institution: Instituto de Física (IF). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The growing need to understand the materiality present in cultural heritage objects has allowed the study and characterization of different materials objects. However, it is increasingly necessary to establish reliable and scientifically based analysis methodologies in the field of heritage sciences. In this sense, the present work proposes the union of spectroscopic techniques in the infrared and X-ray regions with multivariate analysis to correlate the data and better understand the results of each analytical technique. It is intended to process the different results of the analyzes for differentiation of pigments with unsupervised statistical techniques such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) that will be used and their potential evaluated. The data will be tested to find clusters of samples that are representing different pigments. In the study will be used Middle Infrared (FTIR) and X-rays (Energy Dispersion X-ray Fluorescence - ED-XRF) to build regression models for differentiating materials. The FTIR measurements with the ATR module and frontal reflection will be compared to better understand the responses of the frontal reflection module and thus expand its use in the area of cultural heritage. Different data with pre-processing techniques and normalizations will be tested with the objective of attenuating the variability of parameters for the separation of different pigment manufacturers. Pre-processing had an important influence on the results, minimizing differences between the materials.

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