The unsymmetrical complexes Ni(dmdt)(dmio) and Ni(dmstfdt)(dmio) (dmdt = dimethyltetrathiafulvalenedithiolate, dmstfdt = dimethyldiselenadithiafulvalenedithiolate, dmio = 1,3-dithiol-2-one- 4,5-dithiolate) were prepared and characterized analytically and spectroscopically. The complexes exhibit strong third-order nonlinear optical response in the visible and near-infrared spectral regions.
Fullerenes and their derivatives are a class of conjugated electron-accepting molecules that show promise for nonlinear optics in the realm of both the first and second hyperpolarizability.[1±4] At odds with other organic systems, they can exist in two doped states: the standard state in which the dopant is dispersed between the molecules and a more fascinating state in which the electron donor is present inside the carbon cage. In this combined experimental and theoretical study, it is shown that endohedral doping with Li increases the third-order response of C 60 by one order of magnitude. Endohedral doping of Buckminsterfullerene has the triple effect of transferring charge to the carbon cage of C 60 , triggering the distortion of the cage (both phenomena are present also in the exohedral doping) and generating a low potential energy surface for the motion of the Li atom.[5±9]As a consequence, any traces of Li@C 60 are due to averaging over such a motion and can be strongly temperaturedependent if the microscopic value of Li@C 60 is a function of the location of the alkali atom.[8±9] In this particular case, even a nearly constant value of g, the second hyperpolarizability concerning the position of the Li atom is of interest if one considers that exohedral doping was found to increase the second hyperpolarizability of C 60 by a factor of 65, [10] where complete charge transfer occurred. Since in the case of Li@C 60 , only 60 % of the electron goes from the dopant to the LUMO of C 60 , [4,5] a response intermediate between those of the neutral empty cage and the mono-anion may be expected. The availability of three points of g as a function of charging may therefore enable extrapolation of the response to larger charges. The recent breakthrough in the production of macroscopic quantities of Li@C 60[11±13] lead us to measure and calculate the second hyperpolarizability of Li@C 60 . The measurements were performed using z-scan [14,15] and degenerate-four-wave-mixing [16] (DFWM) procedures. The zscan technique provides both the sign and the magnitude of the real and imaginary parts of the third-order susceptibility while DFWM is used to determine its total magnitude. With the spectroscopic techniques, the macroscopic nonlinear optical response, i.e., the third-order susceptibility w, is measured. This quantity is the counterpart of the microscopic, molecular second-order hyperpolarizability. The computational model adopted was a non-standard procedure, which consists of a sum over molecular orbitals scheme. [17] In this approach, the orbitals are calculated ab initio and are then used to generate the transition dipole moments, which are multiplied together, weighed on the proper energy denominators, and finally added to give g. Despite the intense computational resources required, this model allowed us to systematically explore the second hyperpolarizability surface of Li@C 60 generated by the motion of the alkali atom 1.5 from the center of the cage, that is, the region of minimum energy conformation.To measure ...
Olive oil is a basic element of the Mediterranean diet and a key product for the economies of the Mediterranean countries. Thus, there is an added incentive in the olive oil business for fraud through practices like adulteration and mislabeling. In the present work, Laser Induced Breakdown Spectroscopy (LIBS) assisted by machine learning is used for the classification of 139 virgin olive oils in terms of their geographical origin. The LIBS spectra of these olive oil samples were used to train different machine learning algorithms, namely LDA, ERTC, RFC, XGBoost, and to assess their classification performance. In addition, the variable importance of the spectral features was calculated, for the identification of the most important ones for the classification performance and to reduce their number for the algorithmic training. The algorithmic training was evaluated and tested by means of classification reports, confusion matrices and by external validation procedure as well. The present results demonstrate that machine learning aided LIBS can be a powerful and efficient tool for the rapid authentication of the geographic origin of virgin olive oil.
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