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• W2976155382 abstract "With 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 volume-averaging 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." @default.
• W2976155382 created "2019-10-03" @default.
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• W2976155382 date "2020-01-01" @default.
• W2976155382 modified "2023-09-29" @default.
• W2976155382 title "Swarm intelligence integrated micromechanical model to investigate thermal conductivity of multi-walled carbon nanotube-embedded cyclic butylene terephthalate thermoplastic nanocomposites" @default.
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• W2976155382 doi "https://doi.org/10.1016/j.compositesa.2019.105646" @default.
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