Thermal energy storage (TES) is extremely important in concentrated solar power (CSP) plants since it represents the main difference and advantage of CSP plants with respect to other renewable energy sources such as wind, photovoltaic, etc. CSP represents a low-carbon emission renewable source of energy, and TES allows CSP plants to have energy availability and dispatchability using available industrial technologies. Molten salts are used in CSP plants as a TES material because of their high operational temperature and stability of up to 500°C. Their main drawbacks are their relative poor thermal properties and energy storage density. A simple cost-effective way to improve thermal properties of fluids is to dope them with nanoparticles, thus obtaining the so-called salt-based nanofluids. In this work, solar salt used in CSP plants (60% NaNO3 + 40% KNO3) was doped with silica nanoparticles at different solid mass concentrations (from 0.5% to 2%). Specific heat was measured by means of differential scanning calorimetry (DSC). A maximum increase of 25.03% was found at an optimal concentration of 1 wt.% of nanoparticles. The size distribution of nanoparticle clusters present in the salt at each concentration was evaluated by means of scanning electron microscopy (SEM) and image processing, as well as by means of dynamic light scattering (DLS). The cluster size and the specific surface available depended on the solid content, and a relationship between the specific heat increment and the available particle surface area was obtained. It was proved that the mechanism involved in the specific heat increment is based on a surface phenomenon. Stability of samples was tested for several thermal cycles and thermogravimetric analysis at high temperature was carried out, the samples being stable.PACS65.: Thermal properties of condensed matter; 65.20.-w: Thermal properties of liquids; 65.20.Jk: Studies of thermodynamic properties of specific liquids

In this research, different contents of eugenol in the 2.5-25 wt.% range were first incorporated into ultrathin fibers of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) by electrospinning and then subjected to annealing to obtain antimicrobial monolayers. The most optimal concentration of eugenol in the PHBV monolayer was 15 wt.% since it showed high electrospinnability and thermal stability and also yielded the highest bacterial reduction against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). This eugenol-containing monolayer was then selected to be applied as an interlayer between a structural layer made of a cast-extruded poly(3-hydroxybutyrate) (PHB) sheet and a commercial PHBV film as the food contact layer. The whole system was, thereafter, annealed at 160 • C for 10 s to develop a novel multilayer active packaging material. The resultant multilayer showed high hydrophobicity, strong adhesion and mechanical resistance, and improved barrier properties against water vapor and limonene vapors. The antimicrobial activity of the multilayer structure was also evaluated in both open and closed systems for up to 15 days, showing significant reductions (R ≥ 1 and < 3) for the two strains of food-borne bacteria. Higher inhibition values were particularly attained against S. aureus due to the higher activity of eugenol against the cell membrane of Gram positive (G+) bacteria. The multilayer also provided the highest antimicrobial activity for the closed system, which better resembles the actual packaging and it was related to the headspace accumulation of the volatile compounds. Hence, the here-developed multilayer fully based on polyhydroxyalkanoates (PHAs) shows a great deal of potential for antimicrobial packaging applications using biodegradable materials to increase both quality and safety of food products.

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Our approach describes any digital image qualitatively by detecting regions/objects inside it and describing their visual characteristics (shape and colour) and their spatial characteristics (orientation and topology) by means of qualitative models. The description obtained is translated into a description logic (DL) based ontology, which gives a formal and explicit meaning to the qualitative tags representing the visual features of the objects in the image and the spatial relations between them. For any image, our approach obtains a set of individuals that are classified using a DL reasoner according to the descriptions of our ontology.