A comparative study was conducted to determine whether it would be advantageous to grow carbon nanotubes on the bottom surface of anisotropically-etched silicon microchannels to facilitate greater heat removal in electronic cooling applications. The effect of the samples was evaluated based on the fluid temperature rise through the channels, the silicon surface temperature increase above ambient, and the pressure drop. The height and deposition pattern of the nanotubes were the parameters investigated in this study. The working fluid, water, was passed through the microchannels at two different volumetric flow rates (16 mL/min and 28 mL/min). Additionally, two different heat fluxes were applied to the backside of the microchannel (10 W/cm2 and 30 W/cm2). Extensive validation of the baseline channels was carried out using a numerical model, a resistor network model, and repeatability tests. Finally, the maximum enhancement when using carbon nanotubes under single-phase, laminar, internal, forced convection was investigated using basic principles in regard to the additional surface area created by the carbon nanotubes, as well as their high thermal conductivity. For the devices tested, the samples with carbon nanotubes not only had a higher pressure drop, but also had a higher surface temperature. Therefore, the baseline samples had the best performance. Furthermore, based on a basic principles investigation, the increase to thermal performance gained by increasing the surface area with CNTs is overshadowed by the decrease in mass flow rate for a fixed pressure drop. The analysis suggests that the limiting factor for heat transfer in single-phase, laminar pressure driven flows is not convection heat transfer resistance, but the bulk resistance of the fluid.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/16133 |
| Date | 10 July 2007 |
| Creators | Dietz, Carter Reynolds |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Thesis |
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