کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5427108 | 1508617 | 2017 | 13 صفحه PDF | دانلود رایگان |
- Characterization of nanoparticle aggregates by optical light scattering.
- Inverse problem formulated as least squares minimization, solved by Tabu Search.
- Does not necessitate particle size or number measurements or polarization information.
- Tested via numerical experiments for both monodisperse and polydisperse aggregates.
- Capable of characterizing reff >â20 nm when 266 nm light source is used.
Characterization of nanostructures using light scattering experiments without using polarization information and a priori particle size or number measurements is investigated through numerical experiments. The study focuses on particle clusters in the form of carbon nanoparticle aggregates that are generated with Filippov's particle-cluster algorithm. Seven cases of monodisperse aggregates with less than 30 nanoparticles with primary particle radius between 10 and 40Â nm are investigated, together with one polydisperse case with lognormal particle size distribution. In all these cases, the scattering behavior of an ensemble of well separated, similar aggregates are represented by the behavior of a single aggregate considering orientation averaging using discrete dipole approximation. A database is developed and used for the solution of the direct problem considering the high computational time required for the solution. The inverse characterization problem is formulated as a least squares minimization. Use of Tabu Search algorithm along with gradient based Levenberg-Marquardt algorithm is investigated as problem topology is prone to multiple extrema. It is found that the proposed method relying on Tabu search algorithm is able to predict the particle size and number for monodisperse aggregates with effective radius larger than 20Â nm using a UV light source at a wavelength of 266Â nm. The proposed method also characterizes the polydisperse aggregate case with reasonable accuracy.
Journal: Journal of Quantitative Spectroscopy and Radiative Transfer - Volume 198, September 2017, Pages 117-129