Heat transfer at the nanoscale has been one of the primary concerns in the design of nanoelectronics and nanostructured materials for applications such as thermal management and thermoelectric energy conversion. This thesis examines the thermal transport in nanoscale thin films and two-dimensional (2D) materials using an optical pump-probe technique based on frequency domain thermoreflectance (FDTR). The design and implementation of a continuous-wave laser based FDTR system is described in detail. The system is extended to an imaging microscope capable of producing micrometer scale maps of several thermophysical properties simultaneously. An analytical formula, which accounts for experimental noise and uncertainty in the controlled model parameters, is derived to calculate the precision of thermoreflectance measurements.
The FDTR system is used to study the anisotropic heat conduction in periodic nanoscale Mo/Si superlattices and a 2D material, graphene. The measured in-plane thermal conductivity values of the superlattices are in good agreement with calculations taking into account both electron and phonon thermal transport, using a phonon mean free path which depends on the Mo layer thickness. The measurement procedure of graphene is described in detail, including the sample preparation, sensitivity analysis, and parameter fitting. Various graphene flakes supported on SiO2 surfaces and atomically flat Muscovite mica surfaces are measured. The results show that the thermal conductivity of single-layer graphene can be improved by ~3 times by using a mica substrate compared to commonly used SiO2 substrates. In addition, comparison with the reported values of suspended graphene suggest that the out-of-plane flexural phonon modes may contribute at least 70% to the thermal conductivity of graphene.
Finally, the thermal model is modified to include volumetric heating for the measurement of materials without a transducer layer. An amorphous silicon film deposited on fused silica and silicon substrates is measured to validate the model.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/17057 |
| Date | 21 June 2016 |
| Creators | Yang, Jia |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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