Enhanced thermal–mechanical properties of polymer composites with hybrid boron nitride nanofillers

Yan, Haiyan; Tang, Yanxia; Su, Juling; Yang, Xiaoyan

doi:10.1007/s00339-013-8149-6

Cited by 66 publications

(51 citation statements)

References 34 publications

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“…The performance of models was found to be better than that of ANOVA models and is in good agreement with the actual data obtained from the study conducted by Yan et al [15]. Based on the sensitivity and parametric analysis, the dominant input process parameters and the hidden non-linear relationships are unveiled, which further validate the robustness of our proposed models.…”

Section: Discussionsupporting

confidence: 86%

“…The exceptional qualities of BNN have been widely studied and investigated to explore its diverse possible applications in real world. These include applications in electric circuits such as BNNT-based integrated circuits (ICs), structural composite materials and hydrogen storage applications [13][14][15]. These Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/swevo applications of BNN require it to be machined at nanoscale, leading to production of BNN based nano-components of complex geometry and functionality.…”

Section: Introductionmentioning

confidence: 99%

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A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance

Garg

Vijayaraghavan

Lam

et al. 2015

Swarm and Evolutionary Computation

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Section: Discussionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance

Garg

Vijayaraghavan

Lam

et al. 2015

Swarm and Evolutionary Computation

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“…On the other hand, the model by Nan et al does not capture the synergic effect at all while the other model by Chu et al overpredicts the effective thermal conductivity beyond the optimum ratio. The used model has also been validated for two other published experimental results (Yu et al and Yan et al ) of hybrid nanocomposites (Fig. ).…”

Section: Calibration and Validation Of The Modelmentioning

confidence: 90%

“… Comparison of the current model with the experimental results of (a) Yu et al (2008) , (b) Yan et al (2014) . [Color figure can be viewed at http://wileyonlinelibrary.com]…”

Section: Calibration and Validation Of The Modelmentioning

confidence: 92%

Design and development of thermally conductive hybrid nano‐composites in polysulfone matrix

et al. 2018

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A percolating network of hybrid fillers can provide significant synergic enhancement of thermal conductivity in polymer matrix composites. Especially, when platelets and fibers of high aspect ratios are mixed to form a percolating network, the percolation thresholds are small. However, the optimum ratio of platelets to fibers must be acquired for the maximum synergic enhancement. In this work, polysulfone (PSU) matrix‐hybrid fillers composite is designed with high thermal conductivity using a computational model. The calibration of computational model with several experimentally measured thermal conductivities of polymer matrix‐hybrid nanocomposites leads to the composition where maximum synergic effect/maximum thermal conductivity is expected. For the specific PSU–Graphene nano‐platelets (GNPs)/Carbon nano‐tubes (CNTs) hybrid composites synthesized in this study, the composition with maximum thermal conductivity as designed by the model is PSU/8.4% GNPs/1.6% CNTs. The samples produced experimentally around this composition have shown close agreement with the predictions of the model. Sensitivity analyses and parametric studies conducted on the model highlight that the dimensional parameters and the interface resistance of the fillers are the most sensitive to enhance the effective thermal conductivity. POLYM. COMPOS., 40:1419–1432, 2019. © 2018 Society of Plastics Engineers

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“…Yan et al demonstrated an effective method for improving the thermal properties of the epoxy composites by incorporation of hybrid BNNTs-BNNSs nanofillers [99]. The nanofillers BNNTs-BNNSs showed homogeneous dispersion in matrix and a strong interface interaction, resulting in a large enhancement for thermal conductivity, with a 95% enhancement in thermal conductivity by addition of only 1 vol.% loading.…”

Section: The Synergistic Effect Of 2dmentioning

confidence: 99%

Effect of Filler Shape on the Thermal Conductivity of Thermal Functional Composites

Liu

Chen

Zhou

et al. 2017

Journal of Nanomaterials

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With the rapid development of electronic industry, heat dissipation issue becomes more and more important. Thermal functional composites (TFCs) are usually binary composites, filled with thermal conductive additives (nanomaterials) in matrix, and the composites show good thermal performance. The theoretical and experimental results show that the filler shape is one of the most important but easily overlooked factors. In this article, we provide a systematic review of the effect of the filler shape on the thermal conductivity of TFCs, and the heat transfer enhancement based on synergistic effect is also summed up. Finally, the future trends of further improving thermal properties of TFCs are predicted.

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Enhanced thermal–mechanical properties of polymer composites with hybrid boron nitride nanofillers

Cited by 66 publications

References 34 publications

A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance

A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance

Design and development of thermally conductive hybrid nano‐composites in polysulfone matrix

Effect of Filler Shape on the Thermal Conductivity of Thermal Functional Composites

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