Mesostructured silica films have been doped with lead sulfide (PbS) nanocrystals by a two-step impregnation, using the mesopores as nanoreactors for PbS growth. Secondary ion mass spectrometry and transmission electron microscopy characterizations demonstrated nanocrystals growth inside the pores and throughout the film thickness, pointing out the feasibility of an impregnation-based synthesis made possible by the porous properties of mesoporous silica films. The mean particles diameter is 5 nm, which is compatible with the pore dimensions. The mesostructure order was retained after the growth of the nanocrystals, as pointed out by small-angle X-ray scattering measurements. Optical absorption and Z-scan measurements indicated that PbS nanoparticles show a quantum confinement effect, while the films are characterized by high nonlinearities of the optical response. The optical properties of this material can be usefully exploited in several nonlinear optical applications.

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Inverse problems in laser spectroscopy are reported to be successfully solved by application of artificial neural networks, a powerful data processing technique that performs better than traditional variation algorithms of solving inverse problems.Keywords: laser spectroscopy, inverse problems, artificial neural networks 157 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/22/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx Proc. SPIE Vol. 4749 158 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/22/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

We discuss the problems with and the real possibilities of determining oil pollution in situ in coastal marine waters with fluorescence spectroscopy and of using artificial neural networks for data interpretation. In general, the fluorescence bands of oil and aquatic humic substance overlap. At oil concentrations in water from a few to tens of micrograms per liter, the intensity of oil fluorescence is considerably lower than that of humic substances at concentrations that typically are present in coastal waters. Therefore it is necessary to solve the problem of separating the small amount of oil fluorescence from the humic substance background in the spectrum. The problem is complicated because of possible interactions between the components and variations in the parameters of the fluorescence bands of humic substances and oil in water. Fluorescence spectra of seawater samples taken from coastal areas of the Black Sea, samples prepared in the laboratory, and numerically simulated spectra were processed with an artificial neural network. The results demonstrate the possibility of estimating oil concentrations with an accuracy of a few micrograms per liter in coastal waters also in cases in which the contribution from other organic compounds, primarily humic substances, to the fluorescence spectrum exceeds that of oil by 2 orders of magnitude and more.

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