Static and dynamic contact angle measurement on rough surfaces using sessile drop profile analysis with application to water management in low temperature fuel cells

Fuel Cells are a promising alternative energy technology. One of the biggest problems that exists in fuel cell is that of water management. A better understanding of wettability characteristics in the fuel cells is needed to alleviate the problem of water management. Contact angle data on gas diffusion layers (GDL) of the fuel cells can be used to characterize the wettability of GDL in fuel cells. A contact angle measurement program has been developed to measure the contact angle of sessile drops from drop images. Digitization of drop images induces pixel errors in the contact angle measurement process. The resulting uncertainty in contact angle measurement has been analyzed. An experimental apparatus has been developed for contact angle measurements at different temperature, with the feature to measure advancing and receding contact angles on gas diffusion layers of fuel cells.

In-situ measurement and characterization of cloud particles using digital in-line holography

Satellite measurement validations, climate models, atmospheric radiative transfer models and cloud models, all depend on accurate measurements of cloud particle size distributions, number densities, spatial distributions, and other parameters relevant to cloud microphysical processes. And many airborne instruments designed to measure size distributions and concentrations of cloud particles have large uncertainties in measuring number densities and size distributions of small ice crystals. HOLODEC (Holographic Detector for Clouds) is a new instrument that does not have many of these uncertainties and makes possible measurements that other probes have never made. The advantages of HOLODEC are inherent to the holographic method. In this dissertation, I describe HOLODEC, its in-situ measurements of cloud particles, and the results of its test flights. I present a hologram reconstruction algorithm that has a sample spacing that does not vary with reconstruction distance. This reconstruction algorithm accurately reconstructs the field to all distances inside a typical holographic measurement volume as proven by comparison with analytical solutions to the Huygens-Fresnel diffraction integral. It is fast to compute, and has diffraction limited resolution. Further, described herein is an algorithm that can find the position along the optical axis of small particles as well as large complex-shaped particles. I explain an implementation of these algorithms that is an efficient, robust, automated program that allows us to process holograms on a computer cluster in a reasonable time. I show size distributions and number densities of cloud particles, and show that they are within the uncertainty of independent measurements made with another measurement method. The feasibility of another cloud particle instrument that has advantages over new standard instruments is proven. These advantages include a unique ability to detect shattered particles using three-dimensional positions, and a sample volume size that does not vary with particle size or airspeed. It also is able to yield two-dimensional particle profiles using the same measurements.

Non-invasive method to predict viscosity and size using total internal reflection fluorescence microscopy (TIRFM) system

This study develops an automated analysis tool by combining total internal reflection fluorescence microscopy (TIRFM), an evanescent wave microscopic imaging technique to capture time-sequential images and the corresponding image processing Matlab code to identify movements of single individual particles. The developed code will enable us to examine two dimensional hindered tangential Brownian motion of nanoparticles with a sub-pixel resolution (nanoscale). The measured mean square displacements of nanoparticles are compared with theoretical predictions to estimate particle diameters and fluid viscosity using a nonlinear regression technique. These estimated values will be confirmed by the diameters and viscosities given by manufacturers to validate this analysis tool. Nano-particles used in these experiments are yellow-green polystyrene fluorescent nanospheres (200 nm, 500 nm and 1000 nm in diameter (nominal); 505 nm excitation and 515 nm emission wavelengths). Solutions used in this experiment are de-ionized (DI) water, 10% d-glucose and 10% glycerol. Mean square displacements obtained near the surface shows significant deviation from theoretical predictions which are attributed to DLVO forces in the region but it conforms to theoretical predictions after ~125 nm onwards. The proposed automation analysis tool will be powerfully employed in the bio-application fields needed for examination of single protein (DNA and/or vesicle) tracking, drug delivery, and cyto-toxicity unlike the traditional measurement techniques that require fixing the cells. Furthermore, this tool can be also usefully applied for the microfluidic areas of non-invasive thermometry, particle tracking velocimetry (PTV), and non-invasive viscometry.