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Hybrid model for characterization of submicron particles using multiwavelength spectroscopy

The area of particle characterization is expansive; it contains many technologies and methods of analysis. Light spectroscopy techniques yield information on the joint property distribution of particles, comprising the chemical composition, size, shape, and orientation of the particles. The objective of this dissertation is to develop a hybrid scattering-absorption model incorporating Mie and Rayleigh-Debye-Gans theory to characterize submicron particles in suspension with multiwavelength spectroscopy.Rayleigh-Debye-Gans theory (RDG) was chosen as a model to relate the particles joint property distribution to the light scattering and absorption phenomena for submicron particles. A correction model to instrument parameters of relevance was implemented to Rayleigh-Debye-Gans theory for spheres. Behavior of nonspherical particles using RDG theory was compared with Mie theory (as a reference).
A multiwavelength assessment of Rayleigh-Debye-Gans theory for spheres was conducted where strict adherence to the limits could not be followed. Reported corrections to the refractive indices were implemented to RDG to try and achieve Mies spectral prediction for spheres.The results of studies conducted for RDG concluded the following. The angle of acceptance plays an important role in being able to assess and interpret spectral differences. Multiwavelength transmission spectra contains qualitative information on shape and orientation of non-spherical particles, and it should be possible to extract this information from carefully measured spectra. There is disagreement between Rayleigh-Debye-Gans and Mie theory for transmission simulations with spherical scatterers of different sizes and refractive indices.

Identiferoai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-3888
Date01 June 2005
CreatorsGarcia-Lopez, Alicia
PublisherScholar Commons
Source SetsUniversity of South Flordia
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceGraduate Theses and Dissertations
Rightsdefault

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