Raman thermometry analysis: Modelling assumptions revisited

In Raman thermometry, several assumptions are made to model the heat conduction and to extract the thermal conductivity of the samples from the measured data. In this work, the heat conduction in bulk and mesa-like samples was investigated by numerical simulation and measured by the temperature-indu...

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Detalles Bibliográficos
Autores: Jaramillo-Fernandez, Juliana, Chávez-Angel, Emigdio, Sotomayor Torres, C. M.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/199755
Acceso en línea:http://hdl.handle.net/10261/199755
Access Level:acceso abierto
Palabra clave:Raman thermometry
Numerical modelling
Thermal conductivity
Bulk
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spelling Raman thermometry analysis: Modelling assumptions revisitedJaramillo-Fernandez, JulianaChávez-Angel, EmigdioSotomayor Torres, C. M.Raman thermometryNumerical modellingThermal conductivityBulkIn Raman thermometry, several assumptions are made to model the heat conduction and to extract the thermal conductivity of the samples from the measured data. In this work, the heat conduction in bulk and mesa-like samples was investigated by numerical simulation and measured by the temperature-induced Raman shift method, to study the range of applicability of these assumptions. The effects of light penetration depth and finite sample size on the accuracy of the thermal conductivity determination were investigated by comparing the results of the finite element method with the usual analytical approximation for bulk samples. We found that the assumptions used in the analytical model can be applied to extract the thermal conductivity in solids if the following conditions are fulfilled: the ratio of light penetration depth to laser spot radius is smaller than 0.5, the ratio of spot radius to sample thickness is smaller than 0.1, and the ratio of spot radius to sample half width is smaller than 0.01.JJF and CMST acknowledge the Swedish Research Council VR (349-2007-8664 and 2014-5100) and the Linnaeus Center in Advanced Optics and Photonics for financial support. CMST and ECA acknowledge support from the Spanish MINECO and the Catalan AGAUR (FIS2015-70862-P and CSD2010-00044). JJF is especially grateful to Dr. M. Sledzinska and Dr. B Graczykowski for discussions and assistance with the Raman measurements and simulations. JJF thanks Profs. S. Anand and S. Lourdudoss, and Mr. A. Abedin, for providing the bulk and microcrystal samples. ICN2 acknowledges support from the Severo Ochoa Program (MINECO, Grant SEV-2013-0295) and funding from the CERCA Programme/Generalitat de Catalunya.Peer reviewedElsevierSwedish Research CouncilMinisterio de Economía y Competitividad (España)Generalitat de CatalunyaConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202020202018info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/199755reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FIS2015-70862-Pinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/SEV-2013-0295https://doi.org/10.1016/j.applthermaleng.2017.11.033Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1997552026-05-22T06:33:51Z
dc.title.none.fl_str_mv Raman thermometry analysis: Modelling assumptions revisited
title Raman thermometry analysis: Modelling assumptions revisited
spellingShingle Raman thermometry analysis: Modelling assumptions revisited
Jaramillo-Fernandez, Juliana
Raman thermometry
Numerical modelling
Thermal conductivity
Bulk
title_short Raman thermometry analysis: Modelling assumptions revisited
title_full Raman thermometry analysis: Modelling assumptions revisited
title_fullStr Raman thermometry analysis: Modelling assumptions revisited
title_full_unstemmed Raman thermometry analysis: Modelling assumptions revisited
title_sort Raman thermometry analysis: Modelling assumptions revisited
dc.creator.none.fl_str_mv Jaramillo-Fernandez, Juliana
Chávez-Angel, Emigdio
Sotomayor Torres, C. M.
author Jaramillo-Fernandez, Juliana
author_facet Jaramillo-Fernandez, Juliana
Chávez-Angel, Emigdio
Sotomayor Torres, C. M.
author_role author
author2 Chávez-Angel, Emigdio
Sotomayor Torres, C. M.
author2_role author
author
dc.contributor.none.fl_str_mv Swedish Research Council
Ministerio de Economía y Competitividad (España)
Generalitat de Catalunya
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Raman thermometry
Numerical modelling
Thermal conductivity
Bulk
topic Raman thermometry
Numerical modelling
Thermal conductivity
Bulk
description In Raman thermometry, several assumptions are made to model the heat conduction and to extract the thermal conductivity of the samples from the measured data. In this work, the heat conduction in bulk and mesa-like samples was investigated by numerical simulation and measured by the temperature-induced Raman shift method, to study the range of applicability of these assumptions. The effects of light penetration depth and finite sample size on the accuracy of the thermal conductivity determination were investigated by comparing the results of the finite element method with the usual analytical approximation for bulk samples. We found that the assumptions used in the analytical model can be applied to extract the thermal conductivity in solids if the following conditions are fulfilled: the ratio of light penetration depth to laser spot radius is smaller than 0.5, the ratio of spot radius to sample thickness is smaller than 0.1, and the ratio of spot radius to sample half width is smaller than 0.01.
publishDate 2018
dc.date.none.fl_str_mv 2018
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/199755
url http://hdl.handle.net/10261/199755
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FIS2015-70862-P
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/SEV-2013-0295
https://doi.org/10.1016/j.applthermaleng.2017.11.033
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
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