Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods

Autores
Clementi, Luis Alberto; Vega, Jorge Ruben; Orlande, Helcio R. B.; Gugliotta, Luis Marcelino
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The diameter distribution of nanometric particles is estimated from multiangle dynamic light scattering (MDLS) measurements by solving an ill-conditioned nonlinear inverse problem through Tikhonov and Bayesian methods. For both methods, the data inputs are the angle-dependent average diameters of the particle size distribution (PSD), which are in turn calculated from the measured autocorrelation functions of the light intensity scattered by a dilute sample of particles. The performance of both methods were tested on the basis of: (i) three simulated polymer latexes that involved PSDs of different shapes, widths, and diameter ranges; and (ii) two real polystyrene latexes obtained by mixing two well-characterized standards of narrow PSDs (of known nominal diameters and standard deviations). For PSDs exhibiting highly-asymmetric modes, or modes of quite different relative concentrations, the Bayesian method produced PSD estimates better than those obtained through Tikhonov regularization.
Fil: Clementi, Luis Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Vega, Jorge Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Orlande, Helcio R. B.. Federal University of Rio de Janeiro; Brasil
Fil: Gugliotta, Luis Marcelino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Materia
Dynamic Light Scattering
Inverse Problem
Bayesian Method
Tikhonov Regularization Method
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/18819
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/18819
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion MethodsClementi, Luis AlbertoVega, Jorge RubenOrlande, Helcio R. B.Gugliotta, Luis MarcelinoDynamic Light ScatteringInverse ProblemBayesian MethodTikhonov Regularization Methodhttps://purl.org/becyt/ford/2.5https://purl.org/becyt/ford/2The diameter distribution of nanometric particles is estimated from multiangle dynamic light scattering (MDLS) measurements by solving an ill-conditioned nonlinear inverse problem through Tikhonov and Bayesian methods. For both methods, the data inputs are the angle-dependent average diameters of the particle size distribution (PSD), which are in turn calculated from the measured autocorrelation functions of the light intensity scattered by a dilute sample of particles. The performance of both methods were tested on the basis of: (i) three simulated polymer latexes that involved PSDs of different shapes, widths, and diameter ranges; and (ii) two real polystyrene latexes obtained by mixing two well-characterized standards of narrow PSDs (of known nominal diameters and standard deviations). For PSDs exhibiting highly-asymmetric modes, or modes of quite different relative concentrations, the Bayesian method produced PSD estimates better than those obtained through Tikhonov regularization.Fil: Clementi, Luis Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Vega, Jorge Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Orlande, Helcio R. B.. Federal University of Rio de Janeiro; BrasilFil: Gugliotta, Luis Marcelino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaTaylor & Francis Ltd2012-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/18819Clementi, Luis Alberto; Vega, Jorge Ruben; Orlande, Helcio R. B.; Gugliotta, Luis Marcelino; Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods; Taylor & Francis Ltd; Inverse Problems In Science And Engineering; 20; 2; 10-2012; 973-9901741-5977CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/abs/10.1080/17415977.2012.658518info:eu-repo/semantics/altIdentifier/doi/10.1080/17415977.2012.658518info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-05T10:47:30Zoai:ri.conicet.gov.ar:11336/18819instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-11-05 10:47:31.22CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods
title Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods
spellingShingle Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods
Clementi, Luis Alberto
Dynamic Light Scattering
Inverse Problem
Bayesian Method
Tikhonov Regularization Method
title_short Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods
title_full Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods
title_fullStr Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods
title_full_unstemmed Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods
title_sort Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods
dc.creator.none.fl_str_mv Clementi, Luis Alberto
Vega, Jorge Ruben
Orlande, Helcio R. B.
Gugliotta, Luis Marcelino
author Clementi, Luis Alberto
author_facet Clementi, Luis Alberto
Vega, Jorge Ruben
Orlande, Helcio R. B.
Gugliotta, Luis Marcelino
author_role author
author2 Vega, Jorge Ruben
Orlande, Helcio R. B.
Gugliotta, Luis Marcelino
author2_role author
author
author
dc.subject.none.fl_str_mv Dynamic Light Scattering
Inverse Problem
Bayesian Method
Tikhonov Regularization Method
topic Dynamic Light Scattering
Inverse Problem
Bayesian Method
Tikhonov Regularization Method
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.5
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The diameter distribution of nanometric particles is estimated from multiangle dynamic light scattering (MDLS) measurements by solving an ill-conditioned nonlinear inverse problem through Tikhonov and Bayesian methods. For both methods, the data inputs are the angle-dependent average diameters of the particle size distribution (PSD), which are in turn calculated from the measured autocorrelation functions of the light intensity scattered by a dilute sample of particles. The performance of both methods were tested on the basis of: (i) three simulated polymer latexes that involved PSDs of different shapes, widths, and diameter ranges; and (ii) two real polystyrene latexes obtained by mixing two well-characterized standards of narrow PSDs (of known nominal diameters and standard deviations). For PSDs exhibiting highly-asymmetric modes, or modes of quite different relative concentrations, the Bayesian method produced PSD estimates better than those obtained through Tikhonov regularization.
Fil: Clementi, Luis Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Vega, Jorge Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Orlande, Helcio R. B.. Federal University of Rio de Janeiro; Brasil
Fil: Gugliotta, Luis Marcelino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
description The diameter distribution of nanometric particles is estimated from multiangle dynamic light scattering (MDLS) measurements by solving an ill-conditioned nonlinear inverse problem through Tikhonov and Bayesian methods. For both methods, the data inputs are the angle-dependent average diameters of the particle size distribution (PSD), which are in turn calculated from the measured autocorrelation functions of the light intensity scattered by a dilute sample of particles. The performance of both methods were tested on the basis of: (i) three simulated polymer latexes that involved PSDs of different shapes, widths, and diameter ranges; and (ii) two real polystyrene latexes obtained by mixing two well-characterized standards of narrow PSDs (of known nominal diameters and standard deviations). For PSDs exhibiting highly-asymmetric modes, or modes of quite different relative concentrations, the Bayesian method produced PSD estimates better than those obtained through Tikhonov regularization.
publishDate 2012
dc.date.none.fl_str_mv 2012-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/18819
Clementi, Luis Alberto; Vega, Jorge Ruben; Orlande, Helcio R. B.; Gugliotta, Luis Marcelino; Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods; Taylor & Francis Ltd; Inverse Problems In Science And Engineering; 20; 2; 10-2012; 973-990
1741-5977
CONICET Digital
CONICET
url http://hdl.handle.net/11336/18819
identifier_str_mv Clementi, Luis Alberto; Vega, Jorge Ruben; Orlande, Helcio R. B.; Gugliotta, Luis Marcelino; Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods; Taylor & Francis Ltd; Inverse Problems In Science And Engineering; 20; 2; 10-2012; 973-990
1741-5977
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/abs/10.1080/17415977.2012.658518
info:eu-repo/semantics/altIdentifier/doi/10.1080/17415977.2012.658518
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis Ltd
publisher.none.fl_str_mv Taylor & Francis Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.082534

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