From micro to macro: Physical-chemical characterization of wheat starch-based films modified with PEG200, sodium citrate, or citric acid.

Needing to extend the shelf-life of packaged food and the evolving consumer demands led researchers to seek innovative, eco-friendly, and biocompatible packaging solutions. Starch is among the most promising natural and renewable alternatives to non-degradable plastics. Here, we deeply study the structural features of starch films modified by adding citric acid (CA) or sodium citrate (SC) as a cross-linker and polyethylene glycol 200 (PEG200) as a plasticizer and obtained through solvent casting. The substances' influence on starch films was evaluated through Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) and Solid-state Nuclear Magnetic Resonance (ss-NMR) spectroscopies. Films' macroscopic properties, such as swelling index, solubility, thermo-mechanical features, and moisture absorption, were also assessed to foresee potential applications. Proper amounts of CA, CS, and PEG200 improve film properties and inhibit starch chains' retrogradation and recrystallization. Besides, the chemical neighbourhood of nuclei observed through ss-NMR significantly changed alongside the polymer chains' mobility. The latter result indicates a different polymer chain structural organization that could justify the film's higher resistance to thermal degradation and elongation at the break. This methodological approach is effective in predicting the macroscopic behaviour of a polymeric material and could be helpful for the application of such products in food preservation.

Sicilian Byzantine Icons through the Use of Non-Invasive Imaging Techniques and Optical Spectroscopy: The Case of the Madonna dell'Elemosina.

The iconographic heritage is one of the treasures of Byzantine art that have enriched the south of Italy, and Sicily in particular, since the early 16th century. In this work, the investigations of a Sicilian Icon of Greek-Byzantine origin, the Madonna dell'Elemosina, is reported for the first time. The study was carried out using mainly non-invasive imaging techniques (photography in reflectance and grazing visible light, UV fluorescence, infrared reflectography, radiography, and computed tomography) and spectroscopic techniques (X-ray fluorescence and infrared spectroscopy). The identification of the constituent materials provides a decisive contribution to the correct historical and artistic placement of the Icon, a treasure of the Eastern European historical community in Sicily. Some hidden details have also been highlighted. Most importantly, the information obtained enables us to define its conservation state, the presence of foreign materials, and to direct its protection and restoration.

Chemometric Tools to Point Out Benchmarks and Chromophores in Pigments through Spectroscopic Data Analyses.

Spectral preprocessing data and chemometric tools are analytical methods widely applied in several scientific contexts i.e., in archaeometric applications. A systematic classification of natural powdered pigments of organic and inorganic nature through Principal Component Analysis with a multi-instruments spectroscopic study is presented here. The methodology allows the access to elementary and molecular unique benchmarks to guide and speed up the identification of an unknown pigment and its recipe. This study is conducted on a set of 48 powdered pigments and tested on a real-case sample from the wall painting in S. Maria Delle Palate di Tusa (Messina, Italy). Four spectroscopic techniques (X-ray Fluorescence, Raman, Attenuated Total Reflectance and Total Reflectance Infrared Spectroscopies) and six different spectrometers are tested to evaluate the impact of different setups. The novelty of the work is to use a systematic approach on this initial dataset using the entire spectroscopic energy range without any windows selection to solve problems linked with the manipulation of large analytes/materials to find an indistinct property of one or more spectral bands opening new frontiers in the dataset spectroscopic analyses.