Enhancement of external spin-orbit coupling effects caused by metal-metal cooperativity

As part of our efforts to discover simple routes to room-temperature phosphors, we have investigated the interaction of bis(pentafluorophenyl)mercury (1) or trimeric perfluoro-o-phenylene mercury (2) with selected arenes (naphthalene, biphenyl, and fluorene). Solution studies indicate that 2, unlike 1, quenches the fluorescence of naphthalene. When compared to 1, the high quenching efficiency of 2 may be correlated to the higher affinity that 2 displays for arenes as well as to more acute external heavy-atom effects caused by the three mercury atoms. In the crystal, the adducts [1.naphthalene], [1.biphenyl], [1.fluorene], and [2.fluorene] form supramolecular binary stacks in which the arene approaches the mercury centers of 1 or 2 to form Hg-C pi-interactions. Analysis of the electrostatic potential surfaces of the individual components supports the involvement of electrostatic interactions. The luminescence spectra of the adducts show complete quenching of the fluorescence and display heavy-atom-induced emission whose energies and vibronic progressions correspond to the phosphorescence of the respective pure arene. The phosphorescence lifetimes are shortened by 3 or 4 orders of magnitude when compared with those of the free arenes. Taken collectively, the structural, photophysical, and computational results herein suggest that the proximity of the three mercury centers serves to enhance the Lewis acidity of 2, which becomes a better acceptor and a more effective heavy-atom effect inducer than 1.     

A discriminant method for classification of Moroccan olive varieties by using direct FT-IR analysis of the mesocarp section

Four cultivars of olives picked up in the Moroccan region of Beni Mellal were subjected to a characterization and classification study. Analytical data were collected by Fourier transform infrared spectroscopy (FTIR), applied on the mesocarp of the fresh olives without any preliminary treatment. The spectral data were pre-treated by derivative elaboration based on the Savitzky-Golay algorithm to reduce noise and increase analytical information. Partial least squares discriminant analysis (PLS-DA) was performed to elaborate the measurement data and assess the discriminant features of the four cultivars. The PLS model was optimized by applying the Martens’ uncertainty test which provided to select the vibrational frequencies giving the most useful information. The optimized model resulted able to separate the four classes and classify new objects into the appropriate defined classes with a percentage prediction of 97%. The proposed method represents a real novelty to classify olives of different varieties by means of a rapid, inexpensive and reliable procedure.