Estimation of the Particle Size Distribution of Colloids from Multiangle Dynamic Light Scattering Measurements with Particle Swarm Optimization

In this paper particle Swarm Optimization (PSO) algorithms are applied to estimate the particle size distribution (PSD) of a colloidal system from the average PSD diameters, which are measured by multi-angle dynamic light scattering. The system is considered a nonlinear inverse problem, and for this...

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Detalhes bibliográficos
Autores: Bermeo, L. A., Caicedo, E., Clementi, Luis Alberto, Vega, Jorge Ruben
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:Argentina
Recursos:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/9921
Acesso em linha:http://hdl.handle.net/11336/9921
Access Level:acceso abierto
Palavra-chave:SWARM INTELLIGENCE
DYNAMIC LIGHT SCATTERING
INVERSE PROBLEM
PARTICLE SWARM OPTIMIZATION ALGORITHM
PARTICLE SIZE DISTRIBUTION
https://purl.org/becyt/ford/2.5
https://purl.org/becyt/ford/2
Descrição
Resumo:In this paper particle Swarm Optimization (PSO) algorithms are applied to estimate the particle size distribution (PSD) of a colloidal system from the average PSD diameters, which are measured by multi-angle dynamic light scattering. The system is considered a nonlinear inverse problem, and for this reason the estimation procedure requires a Tikhonov regularization method. The inverse problem is solved through several PSO strategies. The evaluated PSOs are tested through three simulated examples corresponding to polysty-rene (PS) latexes with different PSDs, and two experimental examples obtained by simply mixing 2 PS standards. In general, the evalu-ation results of the PSOs are excellent; and particularly, the PSO with the Trelea's parameter set shows a better performance than other implemented PSOs.