Measuring the Stability of Supramolecular Complexes in the Proximity of Single-Walled Carbon Nanotubes

The decoration of SWNTs with supramolecular motifs is a common strategy for their subsequent noncovalent functionalization. However, due to the lack of a standard methodology, there are no quantitative measurements showing the extent to which the supramolecular equilibria are affected by one of the host-guest couple being anchored to the SWNT. Here, we use a method we initially developed to quantify association of small organic molecules to the walls of SWNTs to compare association constants of two host-guest systems, a Hamilton receptor-cyanuric acid derivative and a crown ether-ammonium couple, in solution and when the host is covalently attached to the SWNTs. Our data show that association does occur, but the stability of the complexes is significantly affected, as reflected in a sizable reduction in their association constant, when compared to solution.     

Raman Optical Activity (ROA) as a New Tool to Elucidate the Helical Structure of Poly(phenylacetylene)s

Poly(phenylacetylene)s are a family of helical polymers constituted by conjugated double bonds. Raman spectra of these polymers show a structural fingerprint of the polyene backbone which, in combination with its helical orientation, makes them good candidates to be studied by Raman optical activity (ROA). Four different well‐known poly(phenylacetylene)s adopting different scaffolds and ten different helical senses have been prepared. Raman and ROA spectra were recorded and allowed to establish ROA‐spectrum/helical‐sense relationships: a left/right‐handed orientation of the polyene backbone (M_helix/P_helix) produces a triplet of positive/negative ROA bands. Raman and ROA spectra of each polymer exhibited the same profile, and the sign of the ROA spectrum was opposite to the lowest‐energy electronic circular dichroism (ECD) band, indicating a resonance effect. Resonance ROA appears then as an indicator of the helical sense of poly(phenylacetylene)s, especially for those with an extra Cotton band in the ECD spectrum, where a wrong helical sense is assigned based on ECD, while ROA alerts of this misassignment.     

Comparison of a Rapid Light-Induced and Forced Test to Study the Oxidative Stability of White Wines

The oxidation processes of white wines can occur during storage and commercialization due to several factors, and these can negatively affect the color, aroma, and quality of the wine. Wineries should have faster and simpler methods that provide valuable information on oxidation stability of wines and allow fast decision-making procedures, able to trigger suitable technological interventions. Using a portable prototype instrument for light irradiations at different wavelengths and times was considered and evaluated on sensorial, spectrophotometric, and colorimetric parameters of white wines. The sensorial analysis revealed that white and light blue were the most significant, after only 1 h of irradiation. The experimental results showed that hydrogen peroxide could enhance the effect of light treatment, allowing a contemporary evaluation of the oxidation stability of wine against light and chemical stresses. As expected, a good correlation (R² > 0.89) between optical density at 420 nm and b* parameter was highlighted. The synergic effect of light and H₂O₂ was also studied on the hydrolyzable and condensed tannins’ additions to white wine. The proposed methodology could be used to evaluate the oxidative stability of white wines, but also to evaluate the effect of some oenological adjuvants on wine stability.     

Mechanically Interlocked Single‐Wall Carbon Nanotubes

Extensive research has been devoted to the chemical manipulation of carbon nanotubes. The attachment of molecular fragments through covalent‐bond formation produces kinetically stable products, but implies the saturation of some of the C? C double bonds of the nanotubes. Supramolecular modification maintains the structure of the SWNTs but yields labile species. Herein, we present a strategy for the synthesis of mechanically interlocked derivatives of SWNTs (MINTs). In the key rotaxane‐forming step, we employed macrocycle precursors equipped with two π‐extended tetrathiafulvalene SWNT recognition units and terminated with bisalkenes that were closed around the nanotubes through ring‐closing metathesis (RCM). The mechanically interlocked nature of the derivatives was probed by analytical, spectroscopic, and microscopic techniques, as well as by appropriate control experiments. Individual macrocycles were observed by HR STEM to circumscribe the nanotubes.     

Investigation of anthropic effects connected with metal ions concentration, organic matter and grain size in Bormida river sediments

An investigation on the sediment composition and grain size was carried out along the Bormida river (Piedmont, Northern Italy). The samples were taken both in the riverbed and on its banks. Multivariate statistical exploratory methods permitted to identify possible sources of primary pollution. In particular, principal component analysis (PCA) showed that there are probably at least three anthropogenic main causes of pollution, one connected with Cr, Ni and Sn, the second with cadmium and the last one with mercury. Some correlations were found between heavy metal ion concentrations and organic matter and/or the sediment grain size. Differences between the samples collected in the riverbed and on the banks were identified and the relationships between the principal components and the distance of the samples from the riverbed and from the hot spot represented by the ACNA industrial site were also analyzed.     

Wildland fire growth prediction method based on Multiple Overlapping Solution

Several Data-Driven Methods have been developed to try to solve the input parameters uncertainty when considering problems like Wildfires Prediction. In general, these methods operate over a large number of input parameters, and consider the most recent known behavior of wildfires. The purpose of the methods is to find the parameter set that best describes the real situation under consideration. Therefore, it is presumed that the same set of values could be used to predict the immediate future.However, because this kind of prediction is based on a single set of parameters, for those parameters that present a dynamic behavior (e.g. wind direction and speed), the new optimized values are not adequate to make a prediction.In this paper we propose an alternative method developed in a new branch of Data-Driven Prediction, which we called Multiple Overlapping Solution. This method combines statistical concepts and HPC (High Performance Computing) to obtain a higher quality prediction.     

Moreau-Yosida Regularization of State-Dependent Sweeping Processes with Nonregular Sets

The existence and the convergence (up to a subsequence) of the Moreau-Yosida regularization for the state-dependent sweeping process with nonregular (subsmooth and positively alpha-far) sets are established. Then, by a reparametrization technique, the existence of solutions for bounded variation continuous state-dependent sweeping processes with nonregular (subsmooth and positively alpha-far) sets is proved. An application to vector hysteresis is discussed, where it is shown that the Play operator with positively alpha-far sets is well defined for bounded variation continuous inputs.