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Discussion on the thermal conductivity enhancement of nanofluids.

Xie H, Yu W, Li Y, Chen L - Nanoscale Res Lett (2011)

Bottom Line: We produced a series of nanofluids and measured their thermal conductivities.Various nanoparticles (NPs) involving Al2O3 NPs with different sizes, SiC NPs with different shapes, MgO NPs, ZnO NPs, SiO2 NPs, Fe3O4 NPs, TiO2 NPs, diamond NPs, and carbon nanotubes with different pretreatments were used as additives.The thermal transport mechanisms in nanofluids were further discussed, and the promising approaches for optimizing the thermal conductivity of nanofluids have been proposed.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Urban Development and Environmental Engineering, Shanghai Second Polytechnic University, Shanghai 201209, China. hqxie@eed.sspu.cn.

ABSTRACT
Increasing interests have been paid to nanofluids because of the intriguing heat transfer enhancement performances presented by this kind of promising heat transfer media. We produced a series of nanofluids and measured their thermal conductivities. In this article, we discussed the measurements and the enhancements of the thermal conductivity of a variety of nanofluids. The base fluids used included those that are most employed heat transfer fluids, such as deionized water (DW), ethylene glycol (EG), glycerol, silicone oil, and the binary mixture of DW and EG. Various nanoparticles (NPs) involving Al2O3 NPs with different sizes, SiC NPs with different shapes, MgO NPs, ZnO NPs, SiO2 NPs, Fe3O4 NPs, TiO2 NPs, diamond NPs, and carbon nanotubes with different pretreatments were used as additives. Our findings demonstrated that the thermal conductivity enhancements of nanofluids could be influenced by multi-faceted factors including the volume fraction of the dispersed NPs, the tested temperature, the thermal conductivity of the base fluid, the size of the dispersed NPs, the pretreatment process, and the additives of the fluids. The thermal transport mechanisms in nanofluids were further discussed, and the promising approaches for optimizing the thermal conductivity of nanofluids have been proposed.

No MeSH data available.


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Dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids [48].
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Figure 6: Dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids [48].

Mentions: Figure 6 shows the dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids [48]. From theoretical prediction, the thermal conductivity of a composite increases with the aspect ratio of the included solid particles [49-51]. Intuition suggests that increasing the milling time should therefore decrease (k - k0)/k0 because of the reduced aspect ratio. Figure 6, however, shows clear peak and valley values in the thermal conductivity enhancement with respect to the milling time for all the studied CNT loadings. For nanofluid at a volume fraction of 0.01, the thermal conductivity enhancements present a peak value of 27.5% and a valley value of 10.4% when the milling times are 10 and 28 h, respectively. The maximal enhancement is intriguingly more than two and half times as the minimal one. Interestingly, when further increased the milling time from 28 to 38 h, (k - k0)/k0 increases from the valley value of 10.4 to 12.8%. Though the increment is not pronounced, it illustrates a difference in tendency from that in the milling time range from 10 to 28 h. Temperature-dependent thermal conductivity enhancement data further indicate that, at all the measured temperatures, nanofluid with CNTs milled for 10 h has the largest increment in thermal conductivity. Glory et al. [52] reported that the enhancement of the thermal conductivity noticeably increases when the nanotube aspect ratio increases. However, the thermal conductivity enhancement behavior of our CNT nanofluid is very different and cannot be explained only by the effect of the aspect ratio.


Discussion on the thermal conductivity enhancement of nanofluids.

Xie H, Yu W, Li Y, Chen L - Nanoscale Res Lett (2011)

Dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids [48].
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3211170&req=5

Figure 6: Dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids [48].
Mentions: Figure 6 shows the dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids [48]. From theoretical prediction, the thermal conductivity of a composite increases with the aspect ratio of the included solid particles [49-51]. Intuition suggests that increasing the milling time should therefore decrease (k - k0)/k0 because of the reduced aspect ratio. Figure 6, however, shows clear peak and valley values in the thermal conductivity enhancement with respect to the milling time for all the studied CNT loadings. For nanofluid at a volume fraction of 0.01, the thermal conductivity enhancements present a peak value of 27.5% and a valley value of 10.4% when the milling times are 10 and 28 h, respectively. The maximal enhancement is intriguingly more than two and half times as the minimal one. Interestingly, when further increased the milling time from 28 to 38 h, (k - k0)/k0 increases from the valley value of 10.4 to 12.8%. Though the increment is not pronounced, it illustrates a difference in tendency from that in the milling time range from 10 to 28 h. Temperature-dependent thermal conductivity enhancement data further indicate that, at all the measured temperatures, nanofluid with CNTs milled for 10 h has the largest increment in thermal conductivity. Glory et al. [52] reported that the enhancement of the thermal conductivity noticeably increases when the nanotube aspect ratio increases. However, the thermal conductivity enhancement behavior of our CNT nanofluid is very different and cannot be explained only by the effect of the aspect ratio.

Bottom Line: We produced a series of nanofluids and measured their thermal conductivities.Various nanoparticles (NPs) involving Al2O3 NPs with different sizes, SiC NPs with different shapes, MgO NPs, ZnO NPs, SiO2 NPs, Fe3O4 NPs, TiO2 NPs, diamond NPs, and carbon nanotubes with different pretreatments were used as additives.The thermal transport mechanisms in nanofluids were further discussed, and the promising approaches for optimizing the thermal conductivity of nanofluids have been proposed.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Urban Development and Environmental Engineering, Shanghai Second Polytechnic University, Shanghai 201209, China. hqxie@eed.sspu.cn.

ABSTRACT
Increasing interests have been paid to nanofluids because of the intriguing heat transfer enhancement performances presented by this kind of promising heat transfer media. We produced a series of nanofluids and measured their thermal conductivities. In this article, we discussed the measurements and the enhancements of the thermal conductivity of a variety of nanofluids. The base fluids used included those that are most employed heat transfer fluids, such as deionized water (DW), ethylene glycol (EG), glycerol, silicone oil, and the binary mixture of DW and EG. Various nanoparticles (NPs) involving Al2O3 NPs with different sizes, SiC NPs with different shapes, MgO NPs, ZnO NPs, SiO2 NPs, Fe3O4 NPs, TiO2 NPs, diamond NPs, and carbon nanotubes with different pretreatments were used as additives. Our findings demonstrated that the thermal conductivity enhancements of nanofluids could be influenced by multi-faceted factors including the volume fraction of the dispersed NPs, the tested temperature, the thermal conductivity of the base fluid, the size of the dispersed NPs, the pretreatment process, and the additives of the fluids. The thermal transport mechanisms in nanofluids were further discussed, and the promising approaches for optimizing the thermal conductivity of nanofluids have been proposed.

No MeSH data available.


Related in: MedlinePlus