A relatively simple subset of nanotechnology - nanofluids - can be obtained by adding nanoparticles to conventional base fluids. The promise of these fluids stems from the fact that relatively low particle loadings (typically <1% volume fractions) can significantly change the properties of the base fluid. This research explores how low volume fraction nanofluids, composed of common base-fluids, interact with light energy. Comparative experimentation and modeling reveals that absorbing light volumetrically (i.e. in the depth of the fluid) is fundamentally different from surface-based absorption. Depending on the particle material, size, shape, and volume fraction, a fluid can be changed from being mostly transparent to sunlight (in the case of water, alcohols, oils, and glycols) to being a very efficient volumetric absorber of sunlight. This research also visualizes, under high levels of irradiation, how nanofluids undergo interesting, localized phase change phenomena. For this, images were taken of bubble formation and boiling in aqueous nanofluids heated by a hot wire and by a laser. Infrared thermography was also used to quantify this phenomenon. Overall, though, this research reveals the possibility for novel solar collectors in which the working fluid directly absorbs light energy and undergoes phase change in a single step. Modeling results indicate that these improvements can increase a solar thermal receiver's efficiency by up to 10%.

Thermoelectric devices (TED's) continue to be an area of high interest in both thermal management and energy harvesting applications. Due to their compact size, reliable performance, and their ability to accomplish sub-ambient cooling, much effort is being focused on optimized methods for characterization and integration of TED's for future applications. Predictive modeling methods can only achieve accurate results with robust input physical parameters, therefore TED characterization methods are critical for future development of the field. Often times, physical properties of TED sub-components are very well known, however the "effective" properties of a TED module can be difficult to measure with certainty. The module-level properties must be included in predictive modeling, since these include electrical and thermal contact resistances which are difficult to analytically derive. A unique characterization method is proposed, which offers the ability to directly measure all device-level physical parameters required for accurate modeling. Among many other unique features, the metrology allows the capability to perform an independent validation of empirical parameters by measuring parasitic heat losses. As support for the accuracy of the measured parameters, the metrology output from an off-the-shelf TED is used in a system-level thermal model to predict and validate observed metrology temperatures. Finally, as an extension to the benefits of this metrology, it is shown that resulting data can be used to empirically validate a device-level dimensionless relationship. The output provides a powerful performance prediction tool, since all physical behavior in a performance domain is captured using a single analytical relationship and can be plotted on a singe graph.