Microanalytical characterization of decorations in handmade ancient floor tiles using inductively coupled plasma optical emission spectrometry (ICP-OES)

Chemistry of Street Art: Neural Network for the Spectral Analysis of Berlin Wall Colors

This research starts with the analysis of some fragments of the Berlin Wall street art for the characterization of the painting materials. The spectroscopic results provide a general description of the paint executive technique but more importantly open the way to a new advantage of Raman application to the analytic analysis of acrylic colors. The study highlights the correlation between peak intensity and compound percentage and explores the powerful application of deep learning for the quantification of a pigment mixture in the acrylic commercial products from Raman spectra acquired with hand-held equipment (BRAVO by Bruker). The study reveals the ability of the convolutional neural network (CNN) algorithm to analyze the spectra and predict the ratio between the coloring compounds. The reference materials for calibration and training were obtained by the dilution of commercial acrylic colors commonly practiced by street artists, using Schmincke brand paints. For the first time, Raman investigation provides valuable insights into calibrations for determining dye dilution in mixtures of commercial products, offering a new opportunity for analytical quantification with Raman hand-held spectrometers and contributing to a comprehensive understanding of artists' techniques and materials in street art.

Preliminary study on analysis and removal of wax from a Carrara marble statue

This preliminary study has mainly focused on the wax identification by nuclear magnetic resonance (NMR) and removal. Wax is used for many purposes in the field of art as protective coatings on wooden, stone or metal objects. From the comparison of the spectra H NMR and in particular with the correspondence of the resonance peaks of the samples taken from the statue and beeswax and paraffin, we can conclude that the wax applied on the statue surface is beeswax. From our data, it can be concluded that, to remove the beeswax, from any stone support, the more effective solvent is the mixture of cyclohexane/ethyl acetate. The removal percentages ranged from 19 to 99%. Lower percentages of removal have been observed in the case of yellow marble, probably because of its high porosity. We can affirm that, this solvent mixture can be employed in real art objects using cotton swabs to remove protective wax.

Assessment of quality of air in Palermo by chemical (ICP-OES) and cytological analyses on leaves of Eucalyptus camaldulensis

In this work, we studied the influence of air pollution on the morpho-structural, biochemical and chemical composition of Eucalyptus camaldulensis leaves. Analyses were carried out on 22 samples collected in Palermo (Italy) area. Considering the mean concentrations (in unwashed leaves) of investigated metals, nutrient elements as Fe (214 mg kg(-1) dry weight (d.w.)), Mn (160 mg kg(-1) d.w.) and Zn (39 mg kg(-1) d.w.) were the most abundant, whereas Pb (5.6 mg kg(-1) d.w.) and Cd (0.072 mg kg(-1) d.w.) showed the lowest concentrations. The values of metal pollution index (MPI) ranged from 6.0 (station no. 15) to 25 (station no. 8) and from 4.0 (station no. 16) to 17 (stations no. 7 and no. 15) for unwashed and washed leaves, respectively. The station no. 8, located in an area interested by traffic mostly caused by the activities of university, showed the highest value of MPI. The station no. 15 (Industrial area) showed the lowest MPI value, which is similar to those determined in the reference stations. Considering that the station considered is located in a large and open area interested only by commercial activities and there are no production activities, this data is not surprising. In this study, the washing of the leaves with distilled water has caused a little reduction of metal concentrations. Microphotography reveals a correlation between zones of necrosis, modified cuticles and accumulations of acid phosphatases in the leaves collected in polluted areas. The diaphanized leaves from the more polluted areas show irregular areolas, several idioblasts both on the ribs and scattered in the mesophyll. With polarized light, we observe many crystal deposits near the ribs.

The distribution of phthalate esters in indoor dust of Palermo (Italy)

In this work, phthalic acid esters (PAEs): dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate, benzyl butyl phthalate, bis(2-ethylhexyl) phthalate, and di-n-octyl phthalate in indoor dust (used as passive sampler) were investigated. The settled dust samples were collected from thirteen indoor environments from Palermo city. A fast and simple method using Soxhlet and GC-MS analysis has been optimized to identify and quantify the phthalates. Total phthalates concentrations in indoor dusts ranged from 269 to 4,831 mg/kg d.w. (d.w. = dry weight). The data show a linear correlation between total PAEs concentration and a single compound content, with the exclusion of the two most volatile components (DMP and DEP) that are present in appreciable amounts only in two samples. These results suggest that most of the PAEs identified in the samples of settled dust originate from the same type of material. This evidence indicates that, in a specific indoor environment, generally is not present only one compound but a mixture having over time comparable percentages of PAEs. Consequently, for routine analyses of a specific indoor environment, only a smaller number of compounds could be determined to value the contamination of that environment. We also note differences in phthalate concentrations between buildings from different construction periods; the total concentration of PAEs was higher in ancient homes compared to those constructed later. This is due to a trend to reduce or remove certain hazardous compounds from building materials and consumer goods. A linear correlation between total PAEs concentration and age of the building was observed (R = 0.71).