University of Extremadura

About: University of Extremadura is a education organization based out in Badajoz, Spain. It is known for research contribution in the topics: Population & Hyperspectral imaging. The organization has 7856 authors who have published 18299 publications receiving 396126 citations. The organization is also known as: Universidad de Extremadura.

Harnessing mechanochemical effects with ultrasound-induced reactions

Abstract: Chemical reactions may experience numerous and varied effects under the influence of ultrasound. This soft radiation, often viewed as a lab trick, induces and improves both physical and chemical transformations by means of efficient agitation, dissolution, mass and heat transfers, and reagents sonolysis, which all arise from the cavitational collapse. An empirical rationale that distinguishes between true chemical effects and mechanical ones, especially in heterogeneous reactions, was introduced more than two decades ago and has been a useful guidance on reporting sonochemical mechanisms. Recent studies have witnessed a truly remarkable data set that boosts sonochemistry over the wall of applied science. This perspective highlights the importance of the so-called false sonochemistry-closely related to mechanochemistry-in modern synthesis, thus illustrating the advantages of using pressure waves in chemistry. Emphasis is put on green transformations, mild polymerization reactions and the selective cleavage of functionalized polymers, which may have an effective impact in process chemistry and represent a realistic option in industry.

Electronic nose for wine ageing detection

Abstract: This paper reports a novel application of an electronic nose (e-nose) for recognition and detection of wine ageing. Two different measurements are performed with the following samples: first, in an experimental cellar the same wine is aged in different type of oak barrel (French and American oak) and during different time (0, 3, 6 and 12 months) and second, several wines made with the same grape variety and from different wine cellars aged in French and American oak. This identification has a great importance for origin denominations for control of frauds. The e-nose is home-developed and home-fabricated for this purpose: a tin oxide multisensor prepared with RF sputtering onto an alumina substrate and doped with chromium and indium is used. The sampling method employed is static headspace followed by a dynamic injection. Linear techniques like principal component analysis (PCA) and nonlinear ones like probabilistic neural networks (PNN) are used for pattern recognition. A classification success rate (correct predicted number over total number of measurements) of 97% and 84% is achieved in detection of the different ageing process experimented by the wines tested.

Monte Carlo simulation of the homogeneous cooling state for a granular mixture

Abstract: The Direct Simulation Monte Carlo (DSMC) method is used to numerically solve the Enskog equation for a granular binary mixture in the homogeneous cooling state (HCS). The fourth velocity moments, the temperature ratio, and also the velocity distribution functions are obtained and compared with approximate analytical results derived recently from a Sonine polynomial expansion [V. Garzo and J. W. Dufty, Phys. Rev. E 60, 5706 (1999)]. The comparison shows an excellent agreement between both approaches, even for strong dissipation or disparate values of the mechanical parameters of the mixture. In contrast to previous studies, the partial temperatures of each species are clearly different, so that the total energy is not equally distributed between both species. Finally, in the same way as in the one-component case, the simulation as well as the theory show a high energy tail of the distribution functions.