Surface-enhanced vibrational techniques for the detection of synthetic organic colorants

The research project object of this thesis is focused on the development of an advanced analytical system based on the combination of an improved thin layer chromatography (TLC) plate coupled with infrared (FTIR) and Raman microscopies for the detection of synthetic dyes. Indeed, the characterization of organic colorants, which are commonly present in mixtures with other components and in a very limited amount, still represents a challenging task in scientific analyses of cultural heritage materials. The approach provides selective spectral fingerprints for each compound, foreseeing the complementary information obtained by micro ATR-RAIRS-FTIR and SERS-Raman analyses, which can be performed on the same separated spot. In particular, silver iodide (AgI) applied on a gold coated slide is proposed as an efficient stationary phase for the discrimination of complex analyte mixtures, such as dyes present in samples of art-historical interest. The gold-AgI-TLC plate shows high performances related both to the chromatographic separation of analytes and to the spectroscopic detection of components. The use of a mid-IR transparent inorganic salt as the stationary phase avoids interferences of the background absorption in FTIR investigations. Moreover, by ATR microscopy measurements performed on the gold-AgI surface, a considerable enhancement in the intensity of spectra is observed. Complementary information can be obtained by Raman analyses, foreseeing a SERS activity of the AgI substrate. The method has been tested for the characterization of a mixture of three synthetic organic colorants widely used in dyeing processes: Brilliant Green (BG1), Rhodamine B (BV10) and Methylene Blue (BB9).

Fault diagnosis of an automotive suspension system

With the development of the embedded application and driving assistance systems, it becomes relevant to develop parallel mechanisms in order to check and to diagnose these new systems. In this thesis we focus our research on one of this type of parallel mechanisms and analytical redundancy for fault diagnosis of an automotive suspension system. We have considered a quarter model car passive suspension model and used a parameter estimation, ARX model, method to detect the fault happening in the damper and spring of system. Moreover, afterward we have deployed a neural network classifier to isolate the faults and identifies where the fault is happening. Then in this regard, the safety measurements and redundancies can take into the effect to prevent failure in the system. It is shown that The ARX estimator could quickly detect the fault online using the vertical acceleration and displacement sensor data which are common sensors in nowadays vehicles. Hence, the clear divergence is the ARX response make it easy to deploy a threshold to give alarm to the intelligent system of vehicle and the neural classifier can quickly show the place of fault occurrence.

PM and material decay: analysis of dry depositions on horizontal and vertical surrogate surfaces through a Deposition Box system

Airborne Particulate Matter (PM), can get removed from the atmosphere through wet and dry mechanisms, and physically/chemically interact with materials and induce premature decay. The effect of dry depositions is a complex issue, especially for outdoor materials, because of the difficulties to collect atmospheric deposits repeatable in terms of mass and homogeneously distributed on the entire investigated substrate. In this work, to overcome these problems by eliminating the variability induced by outdoor removal mechanisms (e.g. winds and rainfalls), a new sampling system called ‘Deposition Box’, was used for PM sampling. Four surrogate materials (Cellulose Acetate, Regenerated Cellulose, Cellulose Nitrate and Aluminum) with different surfaces features were exposed in the urban-marine site of Rimini (Italy), in vertical and horizontal orientations. Homogeneous and reproducible PM deposits were obtained and different analytical techniques (IC, AAS, TOC, VP-SEM-EDX, Vis-Spectrophotometry) were employed to characterize their mass, dimension and composition. Results allowed to discriminate the mechanisms responsible of the dry deposition of atmospheric particles on surfaces with different nature and orientation and to determine which chemical species, and in which amount, tend to preferentially deposit on them. This work demonstrated that “Deposition Box” can represent an affordable tool to study dry deposition fluxes on materials and results obtained will be fundamental in order to extend this kind of exposure to actual building and heritage materials, to investigate the PM contribution in their decay.