Ricerc@Sapienza

In recent years, in the context of the application of Multivariate Curve Resolution (MCR) to hyperspectral image analysis, attention has been more and more put onto the possibility of exploiting not only the spectral but also the spatial information for constraining the algorithmic solution. Examples involve the introduction of different spatial constraints during the iterative Alternating Least Squares (ALS) calculation of the MCR solution or the post-processing of the score images using conventional image processing techniques.

Asbestos technological properties and its relatively low cost was the main reason, in
the past, for its wide utilization in many industrial sectors. Among the sectors, building and
construction ones utilized a lot of asbestos containing materials (ACM). During the construction and
demolition waste (C&DW) recycling process, ACM must be collected and separated from the other
wastes. C&DW materials includes, but are not limited to, bricks, concrete, masonry materials, roofing

The aim of this work is to investigate the stability to simulated solar radiation of some paintings samples through a new methodological approach adopting non-invasive spectroscopic techniques. In particular, commercial watercolours and iron oxide based pigments were used, these last ones being prepared for the experimental by gum Arabic in order to propose a possible substitute for traditional reintegration materials.

The aim of this work was to recognize different polymer flakes from mixed plastic waste through an innovative hierarchical classification strategy based on hyperspectral imaging, with particular reference to low density polyethylene (LDPE) and high-density polyethylene (HDPE). A plastic waste composition assessment, including also LDPE and HDPE identification, may help to define optimal recycling strategies for product quality control.

In this work, hyperspectral imaging in the short wave infrared range (SWIR: 1000-2500 nm) coupled with chemometric techniques was evaluated as an analytical tool to detect and classify different asbestos minerals, such as amosite ((Fe2+)2(Fe2+,Mg)5Si8O22(OH)2)), crocidolite (Na2(Mg,Fe)6Si8O22(OH)2) and chrysotile (Mg3(Si2O5)(OH)4), contained in cement matrices. Principal Component Analysis (PCA) was used for data exploration and Soft Independent Modeling of Class Analogies (SIMCA) for sample classification.

The presence of mortar attached to the surface of recycled aggregates strongly affect their quality, especially in order to reuse them for making new concrete. In this perspective, an innovative sensor-based quality control strategy was developed using hyperspectral imaging (HSI) in the near-infrared range (1000–1700 nm), to evaluate the residual mortar content on the surface of coarse recycled concrete aggregates.

In this work the possibility to apply hyperspectral imaging as a fast and non-destructive technique for the monitoring of the production process at pilot plant scale of an innovative biowaste-derived fertilizer was explored. Different mixtures of urban organic waste, farm organic residues, biochar and vegetable active principles were selected and utilized in two different European countries, Italy and Spain, for the production of the innovative fertilizer.