Most of the sunlight powering natural photosynthesis is absorbed by antenna arrays that transfer, and regulate the delivery of excitation energy to reaction centers in the chloroplast where photosynthesis takes place. Under intense sunlight the plants and certain organisms cannot fully utilize all of the sunlight received by antennas and excess redox species are formed which could potentially harm them. To prevent this, excess energy is dissipated by antennas before it reaches to the reaction centers to initiate electron transfer needed in the next steps of photosynthesis. This phenomenon is called non-photochemical quenching (NPQ). The mechanism of NPQ is not fully understood, but the process is believed to be initiated by a drop in the pH in thylakoid lumen in cells. This causes changes in otherwise nonresponsive energy acceptors which accept the excess energy, preventing oversensitization of the reaction center. To mimic this phenomenon and get insight into the mechanism of NPQ, a novel pH sensitive dye 3'6'-indolinorhodamine was designed and synthesized which in a neutral solution stays in a closed (colorless) form and does not absorb light while at low pH it opens (colored) and absorbs light. The absorption of the dye overlaps porphyrin emission, thus making energy transfer from the porphyrin to the dye thermodynamically possible. Several self-regulating molecular model systems were designed and synthesized consisting of this dye and zinc porphyrins organized on a hexaphenylbenzene framework to functionally mimic the role of the antenna in NPQ. When a dye-zinc porphyrin dyad is dissolved in an organic solvent, the zinc porphyrin antenna absorbs and emits light by normal photophysical processes. Time resolved fluorescence experiments using the single-photon-timing method with excitation at 425 nm and emission at 600 nm yielded a lifetime of 2.09 ns for the porphyrin first excited singlet state. When acetic acid is added to the solution of the dyad, the pH sensitive dye opens and quenches the zinc porphyrin emission decreasing the lifetime of the porphyrin first excited singlet state to 23 ps, and converting the excitation energy to heat. Under similar experimental conditions in a neutral solution, a model hexad containing the dye and five zinc porphyrins organized on a hexaphenylbenzene core decays exponentially with a time constant of 2.1 ns, which is essentially the same lifetime as observed for related monomeric zinc porphyrins. When a solution of the hexad is acidified, the dye opens and quenches all porphyrin first excited singlet states to <40 ps. This converts the excitation energy to heat and renders the porphyrins kinetically incompetent to readily donate electrons by photoinduced electron transfer, thereby mimicking the role of the antenna in photosynthetic photoprotection.

This dissertation describes a novel, low cost strategy of using particle streak (track) images for accurate micro-channel velocity field mapping. It is shown that 2-dimensional, 2-component fields can be efficiently obtained using the spatial variation of particle track lengths in micro-channels. The velocity field is a critical performance feature of many microfluidic devices. Since it is often the case that un-modeled micro-scale physics frustrates principled design methodologies, particle based velocity field estimation is an essential design and validation tool. Current technologies that achieve this goal use particle constellation correlation strategies and rely heavily on costly, high-speed imaging hardware. The proposed image/ video processing based method achieves comparable accuracy for fraction of the cost. In the context of micro-channel velocimetry, the usability of particle streaks has been poorly studied so far. Their use has remained restricted mostly to bulk flow measurements and occasional ad-hoc uses in microfluidics. A second look at the usability of particle streak lengths in this work reveals that they can be efficiently used, after approximately 15 years from their first use for micro-channel velocimetry. Particle tracks in steady, smooth microfluidic flows is mathematically modeled and a framework for using experimentally observed particle track lengths for local velocity field estimation is introduced here, followed by algorithm implementation and quantitative verification. Further, experimental considerations and image processing techniques that can facilitate the proposed methods are also discussed in this dissertation. Unavailability of benchmarked particle track image data motivated the implementation of a simulation framework with the capability to generate exposure time controlled particle track image sequence for velocity vector fields. This dissertation also describes this work and shows that arbitrary velocity fields designed in computational fluid dynamics software tools can be used to obtain such images. Apart from aiding gold-standard data generation, such images would find use for quick microfluidic flow field visualization and help improve device designs.

In an effort to begin validating the large number of discovered candidate biomarkers, proteomics is beginning to shift from shotgun proteomic experiments towards targeted proteomic approaches that provide solutions to automation and economic concerns. Such approaches to validate biomarkers necessitate the mass spectrometric analysis of hundreds to thousands of human samples. As this takes place, a serendipitous opportunity has become evident. By the virtue that as one narrows the focus towards "single" protein targets (instead of entire proteomes) using pan-antibody-based enrichment techniques, a discovery science has emerged, so to speak. This is due to the largely unknown context in which "single" proteins exist in blood (i.e. polymorphisms, transcript variants, and posttranslational modifications) and hence, targeted proteomics has applications for established biomarkers. Furthermore, besides protein heterogeneity accounting for interferences with conventional immunometric platforms, it is becoming evident that this formerly hidden dimension of structural information also contains rich-pathobiological information. Consequently, targeted proteomics studies that aim to ascertain a protein's genuine presentation within disease- stratified populations and serve as a stepping-stone within a biomarker translational pipeline are of clinical interest. Roughly 128 million Americans are pre-diabetic, diabetic, and/or have kidney disease and public and private spending for treating these diseases is in the hundreds of billions of dollars. In an effort to create new solutions for the early detection and management of these conditions, described herein is the design, development, and translation of mass spectrometric immunoassays targeted towards diabetes and kidney disease. Population proteomics experiments were performed for the following clinically relevant proteins: insulin, C-peptide, RANTES, and parathyroid hormone. At least thirty-eight protein isoforms were detected. Besides the numerous disease correlations confronted within the disease-stratified cohorts, certain isoforms also appeared to be causally related to the underlying pathophysiology and/or have therapeutic implications. Technical advancements include multiplexed isoform quantification as well a "dual- extraction" methodology for eliminating non-specific proteins while simultaneously validating isoforms. Industrial efforts towards widespread clinical adoption are also described. Consequently, this work lays a foundation for the translation of mass spectrometric immunoassays into the clinical arena and simultaneously presents the most recent advancements concerning the mass spectrometric immunoassay approach.

Obtaining local electrochemical (EC) information is extremely important for understanding basic surface reactions, and for many applications. Scanning electrochemical microscopy (SECM) can obtain local EC information by scanning a microelectrode across the surface. Although powerful, SECM is slow, the scanning microelectrode may perturb reaction and the measured signal decreases with the size of microelectrode. This thesis demonstrates a new imaging technique based on a principle that is completely different from the conventional EC detection technologies. The technique, referred to as plasmonic-based electrochemical imaging (PECI), images local EC current (both faradaic and non-faradaic) without using a scanning microelectrode. Because PECI response is an optical signal originated from surface plasmon resonance (SPR), PECI is fast and non-invasive and its signal is proportional to incident light intensity, thus does not decrease with the area of interest. A complete theory is developed in this thesis work to describe the relationship between EC current and PECI signal. EC current imaging at various fixed potentials and local cyclic voltammetry methods are developed and demonstrated with real samples. Fast imaging rate (up to 100,000 frames per second) with 0.2×3µm spatial resolution and 0.3 pA detection limit have been achieved. Several PECI applications have been developed to demonstrate the unique strengths of the new imaging technology. For example, trace particles in fingerprint is detected by PECI, a capability that cannot be achieved with the conventional EC technologies. Another example is PECI imaging of EC reaction and interfacial impedance of graphene of different thicknesses. In addition, local square wave voltammetry capability is demonstrated and applied to study local catalytic current of platinum nanoparticle microarray. This thesis also describes a related but different research project that develops a new method to measure surface charge densities of SPR sensor chips, and micro- and nano-particles. A third project of this thesis is to develop a method to expand the conventional SPR detection and imaging technology by including a waveguide mode. This innovation creates a sensitive detection of bulk index of refraction, which overcomes the limitation that the conventional SPR can probe only changes near the sensor surface within ~200 nm.

As miniature and high-heat-dissipation equipment became major manufacture and operation trends, heat-rejecting and heat-transport solutions faced increasing challenges. In the 1970s, researchers showed that particle suspensions can enhance the heat transfer efficiency of their base fluids. However, their work was hindered by the sedimentation and erosion issues caused by the relatively large particle sizes in their suspensions. More recently, nanofluids--suspensions of nanoparticles in liquids-were proposed to be applied as heat transfer fluids, because of the enhanced thermal conductivity that has generally been observed. However, in practical applications, a heat conduction mechanism may not be sufficient for cooling high-heat-dissipation devices such as microelectronics or powerful optical equipment. Thus, the thermal performance under convective, i.e., flowing heat transfer conditions becomes of primary interest. In addition, with the presence of nanoparticles, the viscosity of a nanofluid is greater than its base fluid and deviates from Einstein's classical prediction. Through the use of a test rig designed and assembled as part of this dissertation, the viscosity and heat transfer coefficient of nanofluids can be simultaneously determined by pressure drop and temperature difference measurements under laminar flow conditions. An extensive characterization of the nanofluid samples, including pH, electrical conductivity, particle sizing and zeta potential, is also documented. Results indicate that with constant wall heat flux, the relative viscosities of nanofluid decrease with increasing volume flow rate. The results also show, based on Brenner's model, that the nanofluid viscosity can be explained in part by the aspect ratio of the aggregates. The measured heat transfer coefficient values for nanofluids are generally higher than those for base fluids. In the developing region, this can be at least partially explained by Prandtl number effects. The Nusselt number ( Nu ) results for nanofluid show that Nu increases with increasing nanofluid volume fraction and volume flow rate. However, only DI-H2O (deionized water) and 5/95 PG/H2O (PG = propylene glycol) based nanofluids with 1 vol% nanoparticle loading have Nu greater than the theoretical prediction, 4.364. It is suggested that the nanofluid has potential to be applied within the thermally developing region when utilizing the nanofluid as a heat transfer liquid in a circular tube. The suggested Reynold's number is greater than 100.