Artículos SCI

An object that is immersed in afluid and approaching a substrate mayfind apotential energy minimum at a certain distance due to the balance between attractive and repulsiveCasimir-Lifshitz forces, a phenomenon referred to as quantum trapping. This equilibriumdepends on the relative values of the dielectric functions of the materials involved. Herein, westudy quantum trapping effects in planar nanocomposite materials and demonstrate that they arestrongly dependent on the characteristics of the spatial inhomogeneity. As a model case, weconsider spherical particles embedded in an otherwise homogeneous material. We propose aneffective medium approximation that accounts for the effect of inclusions andfind that anunprecedented and counterintuitive intense repulsive Casimir-Lifshitz force arises as a result ofthe strong optical scattering and absorption size-dependent resonances caused by their presence. Our results imply that the properanalysis of quantum trapping effects requires comprehensive knowledge and a detailed description of the potential inhomogeneity(caused by imperfections, pores, inclusions, and density variations) present in the materials involved

In this work, a mixture of (NH4)3SiF7/(NH4)2SiF6 powders was obtained as a by-product of the Li extraction process from alpha-spodumene aluminosilicate with NH4HF2. The thermal behavior of the powders was analyzed by non-isothermal thermogravimetric experiments. The kinetic parameters that describe the processes involved were obtained using mathematical deconvolution, Friedman's method, combined kinetic analysis, and nonlinear regression optimization. The results show that the process occurs in two partially overlapping steps, the thermal decomposition of (NH4)3SiF7 into (NH4)2SiF6 and the subsequent sublimation of (NH4)2SiF6. The apparent activation energies were 72.6 and 79.8 kJ/ mol for steps 1 and 2, respectively. The apparent pre-exponential factors were 1.19 x 106 and 2.50 x 105 s-1, respectively. The kinetic models indicated that Step 1 follows an A2 model, while Step 2 follows an F0 model. Finally, the resulting kinetic parameters allowed the reconstruction of the original experimental curves and obtaining predictions of curves recorded under other heating programs.