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Description
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.
ContributorsShan, Xiaonan (Author) / Tao, Nongjian (Thesis advisor) / Chae, Junseok (Committee member) / Christen, Jennifer Blain (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2011
Description
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.
ContributorsMahanti, Prasun (Author) / Cochran, Douglas (Thesis advisor) / Taylor, Thomas (Thesis advisor) / Hayes, Mark (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Metal-organic frameworks (MOFs) are a new set of porous materials comprised of metals or metal clusters bonded together in a coordination system by organic linkers. They are becoming popular for gas separations due to their abilities to be tailored toward specific applications. Zirconium MOFs in particular are known for their high stability under standard temperature and pressure due to the strength of the Zirconium-Oxygen coordination bond. However, the acid modulator needed to ensure long range order of the product also prevents complete linker deprotonation. This leads to a powder product that cannot easily be incorporated into continuous MOF membranes. This study therefore implemented a new bi-phase synthesis technique with a deprotonating agent to achieve intergrowth in UiO-66 membranes. Crystal intergrowth will allow for effective gas separations and future permeation testing. During experimentation, successful intergrown UiO-66 membranes were synthesized and characterized. The degree of intergrowth and crystal orientations varied with changing deprotonating agent concentration, modulator concentration, and ligand:modulator ratios. Further studies will focus on achieving the same results on porous substrates.
ContributorsClose, Emily Charlotte (Author) / Mu, Bin (Thesis director) / Shan, Bohan (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
X-ray crystallography is the most widely used method to determine the structure of proteins, providing an understanding of their functions in all aspects of life to advance applications in fields such as drug development and renewable energy. New techniques, namely serial femtosecond crystallography (SFX), have unlocked the ability to unravel the structures of complex proteins with vital biological functions. A key step and major bottleneck of structure determination is protein crystallization, which is very arduous due to the complexity of proteins and their natural environments. Furthermore, crystal characteristics govern data quality, thus need to be optimized to attain the most accurate reconstruction of the protein structure. Crystal size is one such characteristic in which narrowed distributions with a small modal size can significantly reduce the amount of protein needed for SFX. A novel microfluidic sorting platform was developed to isolate viable ~200 nm – ~600 nm photosystem I (PSI) membrane protein crystals from ~200 nm – ~20 μm crystal samples using dielectrophoresis, as confirmed by fluorescence microscopy, second-order nonlinear imaging of chiral crystals (SONICC), and dynamic light scattering. The platform was scaled-up to rapidly provide 100s of microliters of sorted crystals necessary for SFX, in which similar crystal size distributions were attained. Transmission electron microscopy was used to view the PSI crystal lattice, which remained well-ordered postsorting, and SFX diffraction data was obtained, confirming a high-quality, viable crystal sample. Simulations indicated sorted samples provided accurate, complete SFX datasets with 3500-fold less protein than unsorted samples. Microfluidic devices were also developed for versatile, rapid protein crystallization screening using nanovolumes of sample. Concentration gradients of protein and precipitant were generated to crystallize PSI, phycocyanin, and lysozyme using modified counterdiffusion. Additionally, a passive mixer was created to generate unique solution concentrations within isolated nanowells to crystallize phycocyanin and lysozyme. Crystal imaging with brightfield microscopy, UV fluorescence, and SONICC coupled with numerical modeling allowed quantification of crystal growth conditions for efficient phase diagram development. The developed microfluidic tools demonstrated the capability of improving samples for protein crystallography, offering a foundation for continued development of platforms to aid protein structure determination.
ContributorsAbdallah, Bahige G (Author) / Ros, Alexandra (Thesis advisor) / Buttry, Daniel (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2016