Swarm intelligence integrated micromechanical model to investigate thermal conductivity of multi-walled carbon nanotube-embedded cyclic butylene terephthalate thermoplastic nanocomposites

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dc.contributor.authorKim, Seong Yunko
dc.contributor.authorJang, Ji-unko
dc.contributor.authorHaile, Bezawit F.ko
dc.contributor.authorLee, Min Wookko
dc.contributor.authorYang, Beomjooko
dc.date.accessioned2019-12-30T07:20:07Z-
dc.date.available2019-12-30T07:20:07Z-
dc.date.created2019-12-30-
dc.date.created2019-12-30-
dc.date.issued2020-01-
dc.identifier.citationCOMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING, v.128-
dc.identifier.issn1359-835X-
dc.identifier.urihttp://hdl.handle.net/10203/270723-
dc.description.abstractWith the recent demand for miniaturization and integration of electronic devices, there has been a growing interest in device malfunction due to high temperature. In this study, a experimental and theoretical study on the composites with improved thermal conductivity by dispersing multi-walled carbon nanotubes (MWCNTs) in the thermoplastic resin was carried out. A micromechanical model was derived based on the ensemble volum-eaveraging method and the modified Eshelby's tensor reflecting the interface properties. The effects of the waviness, interface, and orientation of fillers on the thermal conductivity of composites were numerically analyzed. A computational intelligence-based particle swarm optimization (PSO) algorithm was adopted to the proposed model for optimizing the model constants. The thermal conductivity of the polymerized cyclic butylene terephthalate (pCBT)/MWCNT composites was experimentally measured according to the content of MWCNT. Finally, the experimentally measured data were utilized in the PSO to improve the predictive capability of the proposed model.-
dc.languageEnglish-
dc.publisherELSEVIER SCI LTD-
dc.titleSwarm intelligence integrated micromechanical model to investigate thermal conductivity of multi-walled carbon nanotube-embedded cyclic butylene terephthalate thermoplastic nanocomposites-
dc.typeArticle-
dc.identifier.wosid000501658900005-
dc.identifier.scopusid2-s2.0-85073979672-
dc.type.rimsART-
dc.citation.volume128-
dc.citation.publicationnameCOMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING-
dc.identifier.doi10.1016/j.compositesa.2019.105646-
dc.contributor.localauthorHaile, Bezawit F.-
dc.contributor.nonIdAuthorKim, Seong Yun-
dc.contributor.nonIdAuthorJang, Ji-un-
dc.contributor.nonIdAuthorLee, Min Wook-
dc.contributor.nonIdAuthorYang, Beomjoo-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorSwarm intelligence-
dc.subject.keywordAuthorMicromechanics-
dc.subject.keywordAuthorThermal conductivity-
dc.subject.keywordAuthorThermoplastic composites-
dc.subject.keywordPlusCOMPOSITES-
dc.subject.keywordPlusCRYSTALLIZATION-
dc.subject.keywordPlusPOLYMERIZATION-
dc.subject.keywordPlusFABRICATION-
dc.subject.keywordPlusANISOTROPY-
dc.subject.keywordPlusINCLUSION-
dc.subject.keywordPlusCONTACT-
dc.subject.keywordPlusFIELD-
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