Browsing by Author "Shih, Wei-Chuan"
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Item 3-D Plasmonic Nanoarchitectures: Fabrication, Characterization, and Applications(2017-12) Arnob, Md Masud Parvez; Shih, Wei-Chuan; Wolfe, John C.; Zagozdzon-Wosik, Wanda; Chen, Ji; Chu, Wei-Kan; Chen, Tai-YenPlasmonic nanostructures are known to concentrate incident light to their surfaces by collective electron oscillation, a.k.a., localized surface plasmon resonance (LSPR). Plasmonic hot-spot refers to locations where electromagnetic fields are particularly enhanced relative to the incident field. Traditional plasmonic nanomaterials are 1D (e.g., colloidal nanoparticles) or 2D (lithographically patterned nanostructure arrays) in nature, which typically result in sparse field concentration patterns. To improve efficiency and better utilization of hot-spots, 3D plasmonic nanoarchitectures are desired, where abundant hot-spots are formed in a 3D volumetric fashion, a feature drastically departing from traditional nanostructures. In this dissertation, two novel 3D plasmonic nanostructures are reported. The first one is NPG nanoparticle, a disk shaped nanostructure with 3D pore-ligament bi-continuous network. NPG disks are made by the low-cost nanosphere lithography (NSL) technique, which is capable of wafer scale production. NPG disks possess larger surface area and high density internal plasmonic hot-spots, which are absent in its bulk counterparts. Due to these unique properties, NPG disks can be potentially used in various surface enhanced Raman spectroscopy (SERS), surface enhanced fluorescence (SEF), and photothermal based applications. To optimize the performance of NPG disks in various applications and understand its plasmonics better, two different modeling techniques, Bruggeman effective medium theory (B-EMT) model and Nanoporous (NP) model, are introduced and evaluated against the experimental data obtained by an electron beam lithography (EBL) compatible fabrication technique for NPG disks. The EBL method can provide large area 2D patterns of randomly distributed nanodisks with flexible interdisk (center to center) distance. Such flexibility is essential to obtain quasi-single NPG disk response, which typically peaks in the near infrared (NIR) spectrum beyond 1 μm, from ensemble measurements by common UV/VIS/NIR spectrometers instead of a specialized NIR spectroscopic microscope. After successful fabrication and modeling, the plasmon enhanced catalysis application of NPG disks is reported in details. The effectiveness of NPG disks in various applications depends on its LSPR peak position. Hence, optimization of an application might require the fine tuning of the peak position. A novel laser based rapid thermal annealing technique is reported to fine tune the LSPR peak position of NPG disks. The second 3D plasmonic nanostructure, reported in this dissertation, is based on the chicken egg shell, a day-to-day waste material. The 3-dimensional (3D) submicron features on the outer shell (OS), inner shell (IS), and shell membrane (SM) regions are sputter coated with gold found to have excellent SERS performance. Moreover, the outer shell substrate is found to be capable of detecting single bacterial cell. This facile way of fabricating 3D plasmonic substrates can facilitate the adoption of 3D plasmonic substrates by researchers in less fortunate countries.Item A FRAMEWORK OF BELIEF PROPAGATION AND GAME THEORY FOR COGNITIVE RADIO SECURITY AND ROUTING(2012-08) Yuan, Zhou; Han, Zhu; Ogmen, Haluk; Shih, Wei-Chuan; Zheng, Rong; Qian, LijunWith the advent of new high data rate wireless applications, as well as growth of existing wireless services, demand for additional bandwidth is increasing rapidly. Existing spectrum allo-cation policies of the Federal Communications Commission (FCC) prohibits unlicensed access to licensed spectrum, constraining them instead to several heavily populated, interference-prone fre-quency bands, which causes spectrum scarcity. However, it has been shown by several spectrum measurement campaigns that the current licensed spectrum usage across time and frequency is in-efficient. Therefore, a concept of unlicensed users temporarily “borrowing” spectrum from incum-bent license holders to improve the spectrum utilization, called dynamic spectrum access (DSA), is proposed. Cognitive radio is a communication paradigm that employs software-defined radio tech-nology in order to perform DSA and others versatile, powerful and portable wireless transceivers. Up until now, most existing works have focused on spectrum sensing and spectrum access, but very few have focused on the higher layer, which is very important for cognitive radio networks. In this dissertation, we use the framework of distributed game theory and belief propagation to explore the routing techniques and the security issues in cognitive radio networks. Firstly, a belief-propagation based defense strategy for the primary user emulation (PUE) attack in cognitive radio networks is proposed, which avoids the deployment of additional sensor networks and expensive hardware in the networks used in the existing literatures. The proposed algorithm can provide low computational complexity and fast execution speed, and the framework is flexible to incorporate to defeat various kinds of attacks for future extension. In the next section, a brand new network-layer attack, named routing toward primary user (RPU) attack, is discovered in cognitive radio networks, in which malicious secondary users will try to route the data to those secondary users which are closer to the primary users in order to increase interference to the primary users. This new attack is very difficult to detect because the malicious nodes may claim that those nodes, to which they forward the packets, behave dishonestly and cause problems in the data transmission. Also a belief-propagation based defense algorithm is proposed in which each node keeps a table recording the feedbacks from the other nodes on the route, exchanges feedback information, computes beliefs and detects the malicious nodes based on the final belief values. Simulation results show that the proposed defense strategy against the RPU attack is effective and efficient in terms of significant reduction in the delay and interference caused by the RPU attack. Finally, we propose a distributed routing algorithm using the network formation game to minimize the aggregate interference from the secondary users to the primary users while keeping the delay along the route low. The proposed distributed routing algorithm can avoid the problems in the centralized routing solution, such as the high cost for building the centralized coordinate nodes, high information-gathering delay, and system breakdown caused by the possible failures in the centralized nodes, and is practically implementable. Simulation results show that the proposed scheme finds better routes in terms of interference to the primary users compared to the shortest path scheme, and the distributed solution shows near optimum compared to the centralized solution. The proposed technologies concern-ing the security issues and the routing algorithms in cognitive radio networks can provide a lot of benefits to society, and will assist the public safety, emergency services, and first responders communities in enabling better communications access to the network, which could potentially translate into additional human lives being saved.Item Advances in Raman and Surface-Enhanced Raman Spectroscopy: Instrumentation, Plasmonic Engineering and Biomolecular Sensing(2014-08) Qi, Ji; Shih, Wei-Chuan; Wolfe, John C.; Han, Zhu; Larin, Kirill V.; Willson, Richard C.; Roysam, BadrinathRaman spectroscopy is a powerful technique for label-free molecular sensing and imaging in various fields. High molecular specificity, non-invasive sampling approach and the need for little or no sample preparation make Raman spectroscopy uniquely advantageous compared to other analytical techniques. However, Raman spectroscopy suffers from the intrinsic limitation of weak signal intensity. Therefore, time-sensitive studies such as diagnosis and clinical applications require improving the throughput of Raman instrumentation. Alternatively, surface-enhanced Raman scattering (SERS) improves the sensitivity by 10^6 to 10^14 times, making the weak Raman intensity no longer a limitation. Nevertheless, it is still a big challenge to engineer plasmonic substrates with high SERS enhancement, good uniformity and reproducibility. This thesis presents advances in: (1) Raman instrumentation towards high-throughput, environmental, biological and biomedical analysis; (2) SERS substrates with high enhancement factor (EF), uniformity and reproducibility; (3) biosensing applications including imaging of cell population and detection of biomolecules towards high time efficiency and sensitivity. In Raman instrumentation, we have built a high-throughput line-scan Raman microscope system and a novel parallel Raman microscope based on multiple-point active-illumination and wide-field hyperspectral data collection. Using the line-scan Raman microscope, we have performed chemical imaging of intact biological cells at the cell population level. We have also demonstrated more flexibility and throughput from the active-illumination Raman microscope in rapid chemical identification and screening of micro and nanoparticles and bacterial spores. Both Raman microscopes have been used to evaluate the large-area SERS uniformity of DC-sputtered gold nanoislands, a low-cost means to fabricate plasmonic substrates. In plasmonic engineering, we have introduced patterned nanoporous gold nanoparticles that feature 3-dimensional mesoporous network with pore size on the order of 10 nm throughput the sub-wavelength nanoparticles. We showed that the plasmonic resonance can be tuned by geometrical engineering of either the external nanoparticle size and shape or the nanoporous network. As an example, we have developed disk-shaped entities, also known as nanoporous gold disks (NPGD) with highly uniform and reproducible SERS EF exceeding 10^8. Label-free, multiplexed molecular sensing and imaging has been demonstrated on NPGD substrates. Using the line-scan Raman microscope and the NPGD substrates, we have successfully developed a label-free DNA hybridization sensor at the single-molecule level in microfluidics. We have observed discrete, individual DNA hybridization events by in situ monitoring the hybridization process using SERS. The advances and promising results presented in this thesis demonstrate potential impact in Raman/SERS imaging and sensing in environmental, biological and biomedical applications.Item Automatic Recognition of Buruli Ulcer Images on Smart Handheld Devices(2013-08) Hu, Rui 1984-; Zouridakis, George; Jansen, Ben H.; Chen, Ji; Shih, Wei-Chuan; Merchant, Fatima AzizBuruli ulcer (BU) disease is a devastating flesh eating bacterial infection that each year affects thousands of people in tropical and subtropical regions. Clinically, BU usually starts as a painless subcutaneous nodule, or as other pre-ulcer forms including papule, plaque, and edema; then it evolves into a painless ulcer, and finally leads to extensive scarring, contractures, and deformations with possible total loss of articulation function. However, treatment with antibiotics at an early stage has been very successful in preventing irreversible deformity and long-term functional disability. Therefore, an easily implemented and rapid diagnostic test that can detect the early stages of BU is of high research priority. In this dissertation, a multistage computerized image-analysis system is proposed that can automatically detect BU in multispectral dermoscopic images. The specific contributions of this work focus on the development of techniques for precise lesion segmentation, efficient image sampling for feature extraction, and skin image modeling for accurate lesion classification. For lesion segmentation, a new method is proposed based on fusion of the partial masks derived from separate segmentations of the color and luminance channels of BU images. This procedure outperformed other techniques when tested on a subset of 26 BU images where the ground truth of manual segmentation by domain expert physicians was known. Internally the system represents BU lesions using the Bag-of-Features methodology, where image features are extracted from image patches. A new strategy for nonuniform image sampling was developed based on occurrence of contextual pixel saliency, whereby patches from dermoscopically interesting regions are sampled more densely. Experiments on a set of 197 images demonstrated an advantage of this method compared to classical grid or random sampling. To obtain more accurate statistics and address the problem of class imbalance due to the small number of BU images compared to non-BU controls in the dataset, a new resampling technique was developed, which increased the sample size of the minority class by splitting lesions in the data space, rather than synthesizing new samples in the feature space. Combined with the feature selection metric of Pearson correlation coefficient, this method resulted in a classifier with more discriminative power. Additionally, a new feature representation of the multispectral images based on optical skin modeling was proposed. In this method, the distribution of physiological characteristics of a lesion, such as melanin, blood volume, and blood oxygenation were estimated for all image pixels, and features were extracted from these reconstructed maps. Experimental results with a set of 197 multispectral images showed that the use of multispectral images provided a significant improvement in classification performance compared to classification based on single white light images. Finally, a modular stand-alone application that includes all system stages has been developed in Matlab that can be further implemented on smart handheld devices.Item Bacteriophage Imaging Immunoassay for Point of Care Diagnostics(2016-08) Kim, Jinsu; Conrad, Jacinta C.; Willson, Richard C.; Vekilov, Peter G.; Varadarajan, Navin; Shih, Wei-Chuan; Ghasemi, HadiPoint-of-care (PoC) devices are used for medical testing at or near the site of patient care. Due to its low cost, simple assay operation, and ease of mass production, the lateral flow immunoassay (LFA) is one of the most widely used and commercially available PoC tests. Nevertheless, traditional LFAs remain limited by two main issues: lack of sensitivity and difficulties in quantification. To develop sensitive and quantitative LFAs, we can consider three strategies (1) new LFA reaction membranes, (2) new reporter materials, and/or (3) new read-out methods. Here, we developed functionalized phage nanoparticles as a new sensitive reporter for LFAs. The use of phage as a scaffold for attachment of multiple bio-recognition and read-out-signal molecules constitutes a novel and innovative approach in LFAs. We first developed fluorescently labeled M13 phage that also are functionalized with anti-analyte antibodies. Individual phage bound to the target analyte (here MS2 virus as a model) and captured on an LFA membrane strip were imaged using epi-fluorescence microscopy. Using automated image processing, we counted the number of bound phage in micrographs as a function of target concentration. The resultant assay was more sensitive than enzyme-linked immunosorbent assays and traditional colloidal-gold nanoparticle LFAs for direct detection of viruses. Next, to understand the high sensitivity, we characterized the binding modes of the phage reporter to targets in the fibrous glass LFA membrane using microscopy and image analysis. We found that the elongated shape of M13 phage coupled with the complex flow promotes reorientation and facilitates the binding. The binding efficiency was also influenced by other assay parameters, such as the length of the phage and their flux through the LFA membrane. The number of bound phage increased as the phage length increased; similarly the number of bound phage increased with the flux [within a particular flow regime]. These results suggested that the increased length and flux of phage increased the chance that phage encountered fibers, thereby enhancing binding efficiency. Next, as a first step towards practical phage LFAs we characterized the stability and durability of phage at elevated temperatures. To reveal the mechanism of temperature-tolerant mutant stability, we characterized the mutant genomes using next-generation sequencing technology. Three potential mechanisms were suggested for the apparent increase in temperature tolerance: gene replication enhancement (due to mutations in gp2); formation of miniphage; and mutations in the p7 coat protein. Finally, as a first step towards a user-friendly and handheld system compatible with PoC use, we incorporated two photon detectors, a multi-pixel photon counter (MPPC) and a photomultiplier tube (PMT), into a smartphone accessory. The sensitivities of those detectors were compared by determining a low level of 1,5-anhydroglucitol (AHG) as a model test reaction in a chemiluminescence assay. The assay sensitivity depended on the detector performance; the PMT detector exhibited ten-fold better sensitivity than the MPPC. These results raise the promising possibility that the developed detectors could be applied to our phage LFA by inserting the appropriate light source and optical filters.Item Big Data Optimization for Modern Communication Networks(2014-12) Liu, Lanchao; Han, Zhu; Shih, Wei-Chuan; Ogmen, Haluk; Prasad, Saurabh; Pan, Miao; Hong, MingyiThe unprecedented big data in modern communication networks presents us opportunities and challenges. An efficient analytic method for the sheer volume of data is of significant importance for smart grid evolution, intelligent communication network management, efficient medical data management, personalized business model design and smart city development. Meanwhile, the huge volume of data makes it impractical to collect, store and processing in a centralized fashion. Moreover, the massive datasets are noisy, incomplete, heterogeneous, structured, prone to outliers, and vulnerable to cyber-attacks. Overall, we are facing a problem in which the classic resources of computation such as time, space, and energy, are intertwined in complex ways with the massive data sources, and new computational mathematical models as well as methodologies must be explored. With the rapid development of the modern communication networks comes the need of novel algorithms for large-scale data processing and optimization. In this thesis, we investigate the application of big data optimization methods for smart grid security and mobile data traffic management. Firstly, we review the parallel and distributed optimization algorithms based on an alternating direction method of multipliers for solving big data optimization problems. The mathematical backgrounds of the algorithms are given, and the implementations on large-scale computing facilities are also illustrated. Next, the applications of big data processing techniques for smart grid security are studied from two perspectives: how to exploit the inherent structure of the data, and how to deal with the huge size of the data sets. Explored problems are the sparse optimization approach for false data injection detection, and the distributed parallel approach for the security-constrained optimal power flow problem, respectively. Finally, we consider big data optimization methods for data traffic management in mobile cloud computing by two specific application cases: the mobile data offloading in a software defined network at the network edge, and the management of mobile cloud service request allocation and response routing. It is shown by numerical results that effective management and processing of ‘big data’ have the potential to significantly improve smart grid security as well as resource utilization and service quality of the mobile cloud computing.Item Characterization of Amorphous Carbon Films for Mask Protection during Ion Beam Bombardment(2017-05) Kusko, Rebecca Elizabeth; Wolfe, John C.; Shih, Wei-Chuan; Wood, Lowell T.The field of lithography is in simplest terms the use of a beam, incident on a mask, to transfer the mask pattern onto the substrate. This process is utilized by every semiconductor company to create the microchips, which make modern life possible. Though photons are the industry standard, atom/ion beam lithography is a specific niche wherein atoms or ions are used to transfer a mask pattern. Although this technique grants excellent flexibility as far as depth of field and diffraction limit, the use of massive particles causes mask damage, limiting commercial applications of the method. To address this problem, we refine a process to coat masks with diamond-like carbon (DLC) to protect them from ion bombardment. This continues the work of Wasson, Hudek, Nounu, and Abichandani, who pioneered deposition techniques to create amorphous carbon films with low initial compressive stress, which remains constant to very high ion doses. In particular, Nounu and Abichandani’s coating technique is repeated but more fully characterized, refined to eliminate the effects of mask charging, and improved with respect to radiation resistance. Further stress measurements are taken, with particular emphasis on in-situ, in vacuum measurements of film response to ion bombardment.Item Computational Analysis of Tissue Remodeling in the Rat Brain after Mild Traumatic Injury(2017-12) Grama, Kedar Balaji; Roysam, Badrinath; Mayerich, David; Ziburkus, Jokubas; Dash, Pramod K.; Shih, Wei-ChuanAnalysis of pathology in the brain at the cellular scale can yield rich insight into the tissue pathology effects of commonly used drug therapies for brain injury. We propose methods to computationally reconstruct whole rat brains slices and analyze cell populations from 2D fluorescence microscopy images. The proposed methods are applied to a group of rats with mild traumatic brain injury and a profile of cell population alterations are presented.Item Data-Driven, Label Consistent, Dictionary Learning Methods for Analysis of Biological Datasets(2016-08) Megjhani, Murad; Roysam, Badrinath; Contreras-Vidal, Jose L.; Shih, Wei-Chuan; Mayerich, David; Leasure, J. Leigh; Burks, JaredThe goal of this thesis is to develop a data-driven, label consistent, and dictionary learning based framework that can be applied on a variety of signal analysis problems. Current methods based on analytical models do not adequately take the variability within and across datasets into consideration when designing signal analysis algorithms. This variability can be added as a morphological constraint to improve the signal analysis algorithms. In particular, this work focuses on three different applications: 1) we present a method for large-scale automated three-dimensional (3-D) reconstruction and profiling of microglia populations in extended regions of brain tissue for quantifying arbor morphology, sensing activation states, and analyzing the spatial distributions of cell activation patterns in tissue; this work provided an opportunity to profile the distribution of microglia in the controlled and device implanted brain. 2) we present a novel morphological constrained spectral unmixing (MCSU) algorithm that combines the spectral and morphological cues in the multispectral image data cube to improve the unmixing quality, this work provided an opportunity to identify new therapeutic opportunities for pancreatic ductal adenocarcinoma (PDAC) from the images collected from humans; and finally, 3) we developed a framework to analyze neuronal response from electroencephalography (EEG) datasets acquired from the infants ranging from 6-24 months. We demonstrated that combining different frequency bands from different spatial locations, yields better classification results, instead of the traditional approach where either one or two frequency bands are used. Using an adaptation of Tibshirani’s Sparse Group LASSO algorithm, we uncovered different spatial and bio markers for understanding a human infant’s brain. These bio-markers can be used for developmental stages of infants and further analysis is required to study the clinical aspects of infant’s social and cognitive development. This work establishes the fundamental mathematical basis for the next generation of algorithms that can leverage the morphological cues from the biological datasets. The algorithm has been embedded into the open source FARSIGHT toolkit with an intuitive graphical user interface.Item DESIGN, SYNTHESIS, AND CHARACTERIZATION OF ORGANIC REDOX MATERIALS FOR AQUEOUS FLOW BATTERY(2016-12-13) Lee, Kuan-yi; Yao, Yan; Shih, Wei-Chuan; Miljanić, Ognjen Š.A redox flow battery (RFB) is a rechargeable device that features soluble electroactive materials are store separately from the reactor. With this flexible layout, power density and energy density are decoupled. However, commercial vanadium flow batteries are expensive due to the high cost of the electrolyte and membrane, preventing widespread adoption of this technology. Due to the acidic electrolyte, safety and severe corrosion is also a problem. In this work, I present the synthesis and characterization of organic compounds as low-cost anolyte materials for aqueous RFBs with neutral electrolytes. The organic redox materials were then synthesized with high solubility of up to 1.6 M in water. 50 stable cycles with 99.6% capacity retention and the coulombic efficiency higher than 99.7% were demonstrated. The theoretical energy density is projected to be as high as 44.86 Wh/L. This work paves the way for developing organic redox materials for low-cost aqueous RFBs.Item Detection and quantification of Pb2+ in Drinking Water Using Dark Field Smartphone Microscope(2017) Nguyen, Hoang; Shih, Wei-ChuanWater is the essence of life, but easy to become contaminated. Lead (Pb) is the most dangerous source of water contamination. There is a significant unmet need for Pb2+ sensing device that is portable, affordable, and ideally, available to the general population. Such a device will enable on-demand Pb2+ detection in virtually any environmental setting and empower individuals to examine the safety of drinking water whenever and wherever needed.Item Developing Label-free Imaging Techniques to Study Biological and Energy Conversion Processes(2021-12) Yang, Xu; Shan, Xiaonan; Chen, Shuo; Mayerich, David; Shih, Wei-Chuan; Yao, YanObtaining in situ characteristics of Lithium metal batteries (LMBs) is extremely important for understanding basic surface reactions involved in solid electrolyte interphase (SEI) formation, lithium nucleation/plating and thus overall cycling performance improvement of the battery cell. This thesis demonstrates a new characterization technique based on a principle that is completely different from the conventional EC detection technologies, plasmonic-based electrochemical imaging (PECI). It images local reactions (both faradaic and non-faradaic) without using a scanning microelectrode. Utilizing the reflectivity 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. SEI layer formation dynamics as well as its correlation with the afterwards lithium plating and nucleation have been successfully characterized in the form of spatial resolved electrochemical current images at various fixed potentials and local cyclic voltammetry methods are developed and demonstrated with real samples. Fast imaging rate (up to 106 frames per second) with 0.2×3μm spatial resolution have been achieved in both tradition electrolyte (1M LiPF6 in EC/DMC) and engineered electrolyte systems, including highly concentrated electrolyte (4M LiFSI in DME) , and additive added electrolytes. An advanced localized high concentration electrolyte composed of 1M LiTFSI in 1,2 DME-TTE have also been characterized in support of the discovery of advanced ether-based electrolyte performances. This dissertation also describes a related but different research project that develops a facile method to test the possibility of metal plasmon induced by intrinsic lithium on non-plasmon surfaces. A third project of this dissertation is to develop a method to provide local insights on oxygen evolution reaction electrocatalyst design and material discovery using total internal reflection. The last part constitutes the expansion of conventional microscope to single cell impedance and cancer metabolism screening. Different phases of cell-substrate adhesion were successfully extracted via a conductive polymer (PEDOT:PSS) and using HeLa cell line. Using a facile imaging method, the metabolic pathway switch has also been observed in the HeLa cell line in the presence of glucose transporter inhibitor and drug dosage for 14 hours.Item Development of a Prototype Manufacturing Process for Reliable Optical-Fiber Based Neural Probes(2015-12) Awale, Apeksha S.; Wolfe, John C.; Shih, Wei-Chuan; Zagozdzon-Wosik, Wanda; Miller, John H., Jr.; Dragoi, ValentinThe function of a neuron depends on its microcircuitry – the inputs it receives from local and long-range connections and the outputs it sends to other neurons. Mapping these connections is typically done by stimulating a population of neurons chemically, electrically, or optically, and recording the induced extracellular action potentials with implanted metallic probes. The probes may be cylindrical needles or thin planar blades. The needles have an advantage for deep structures since their circular cross-section minimizes friction, hence insertion force, while planar probes provide much greater design flexibility at low cost by leveraging semiconductor manufacturing technology. In this thesis, we explore the possibility of manufacturing cylindrical probes with dense thin film electrode patterns on fine optical fibers, thus, providing the design flexibility of planar probes in the cylindrical format required for deep brain applications. Our group reported the fabrication of cylindrical probes with 4-integrated electrodes on 60 µm optical fibers at EIPBN-2013. These proof-of-concept optrodes were used to detect photo-simulated electrical activity of neurons in the primary visual cortex of Olemur garnettii, a non-prosimian primate. However, processing times were unacceptably long, about 1 month for a batch of 4 probes, and all experienced short-term electrode failure in cerebro-spinal fluid through insulator delamination, which remains a major obstacle to long-term viability of many state-of-the-art probe technologies. In this thesis we report optimized processes that reduce the time and increase batch size for fabricating 4-channel optrodes that result in a projected processing time of 80 minutes for a batch of 16 probes-about 5 minutes/probe. Our most important achievement was the development of a rugged, pin-hole free dielectric coating with stable impedance in phosphate-buffered saline over a period of 10 days under moderate (6mA/cm2) electrical stimulation at frequencies from 200-10,000 Hz. Electrode impedance on a 60 µm fiber was unchanged after 6 repeated insertions to a depth of 3.8 cm in agar gel (Landor Trading Company), which simulates the consistency of brain tissue. Scanning electron microscopy showed that scratching was absent on probes that had been inserted to a depth of 3.8 cm in 75 µm and 438 µm stainless steel canulae.Item Development of Flexible Neural Probes for Stimulation and Recording in the Central Nervous System(2013-08) Gheewala, Mufaddal; Wolfe, John C.; Shih, Wei-Chuan; Sheth, Bhavin R.; Dani, John A.; Randall, John N.; Pang, Stella W.; Purushothaman, GopathyThe functionality of cortical neurons depends on the strength of its local and long-range synapses and the interpretation of the physical and functional anatomy depends on the understanding of these connections. Optogenetics uses genetic manipulations to insert opsin containing ion channels into neurons. Then light can be used to optically gate ion-transport across the plasma membrane to stimulate or silence spiking activity with greater cellular specificity and spatio-temporal resolution than previously possible. While great progress has been made in the genetic methods used in optogenetics, little progress has been made in improving the devices (optrodes) used to simultaneously photostimulate and record neural activity. In this dissertation we describe the development of a new probe concept based on the integration of micrometer-scale thin film electrodes and associated interconnect wiring on the cylindrical surface of fine optical fibers with tight manufacturing tolerances. The use of optical fibers as probe substrates provides high intensity, multi-spectral light delivery with essentially no coupling loss, as well as the strength and stiffness required for deep-brain applications. High resolution permits a very high electrode count on thin fibers, and high dimensional precision enables accurate 3-D localization of neuronal sources. Moreover, the technology is compatible with high throughput manufacturing at very low cost, an important consideration for wide dissemination of the technology, particularly for linear and 2D-array applications. A second crucial development is the design and implementation of a multi-electrode interface between thin-film wiring on the (cylindrical) probe and state-of-the-art neuro-amplifier and signal processing systems. Two-channel prototypes have been fabricated and used in preliminary experiments to 1) record photostimulated neural activity in a group of genetically identified neurons in the primate primary visual cortex at the Vanderbilt University School of Medicine (VUSM), and 2) demonstrate source localization in the rat hippocampus at the Baylor College of Medicine (BCM). The prototypes had 15x15 µm2 gold electrodes on 65 µm optical fibers with lengths up to 3 cm. In future work, we propose to further reduce probe diameter to the ~30 µm range to develop probes with advanced functionality and extend the technology to 1- and 2-D arrays.Item Development of Multi-Electrode Neural Probe on Optical Fiber Substrate for Brain-Machine Interfaces(2018-05) Tisa, Tamanna Afrin; Wolfe, John C.; Shih, Wei-Chuan; Zagozdzon-Wosik, Wanda; Charlson, Earl J.; Wood, Lowell T.; Ardebili, HalehBrain-machine interfaces (BMIs) aim to restore communication and control of prosthetic devices to individuals with neurological injury or disease, by recording the neural activity, and mapping or decoding it in to a motor command. One of the great challenges in this effort is to develop reliable neural probes that are capable of processing the activity of large ensembles of cortical neurons. In this dissertation, we reported a method for fabricating highly reliable neural probes with integrated, thin film conductor and dielectric coatings on the cylindrical surface of fine optical fibers for brain-machine interfacing. The use of optical fibers as probe substrates provide the strength and stiffness required for deep-brain applications, as well as the high intensity, multi-spectral light delivery with essentially no coupling loss is useful for optogenetics application in neuroscience. Early probes were fabricated on 65 µm optical fiber substrates with polyimide jackets. Electrodes were defined over this jacket, and high quality in-vivo recordings were acquired in area V1 of the Greater Northern Galago (Galago garnetti). Microscopic examination of the probes after extraction from the brain, showed that the jacket had cracked and delaminated; the glass itself may have cracked. Invariably this happened near the probe tip, suggesting that micro-cracking of the unprotected fiber end was the cause of the problem. So, a new jacket of cross-linked plasma-deposited styrene was developed. This layer was impervious to water vapor, as well as hot acids and bases. Single channel probes fabricated with this jacket survived a battery of reliability tests, including continuous soaking in PBS for 30 days, multiple insertions in agar gel and cannulas, disinfection, and marinating overnight in a whole mouse brain in the Dragoi lab. Moreover, test-to-test and lot-to-lot variation of the 2 kHz impedance was less than 1 % (3). High quality, in-vitro spike recordings were acquired in a living mouse brain slice at the Dragoi lab. Thus, reliability of the contact fabrication process has been established. In this dissertation, we also reported the extension of the technology that we developed for single channel prototypes to probes with a large number (>30) of micrometer-scale contacts that are needed to map laminar circuits in the brain. For fabricating those multi-electrode neural probes, significant advancement in alignment technology was required. The near-atomic straightness of fiber holder and accurate registration of the mask pattern with the V-grooves ensures that the printed pattern will be centered on the bottom of the fiber. The overlay of patterns on the fiber was ensured, a) longitudinally by using fiber stops, high precision ball bearings which were hold to lithographically defined pits at the tip-end of each V-groove, b) rotationally by using a high precision cubic bead glued to the end of the fiber as the reference. SEM images showed that longitudinal and lateral pattern overlay error was always below 2 µm without any outliers.Item Fabrication of Multi-point Side-Firing Optical Fiber by Laser Micro- ablation(Optics Letters, 1/16/2018) Nguyen, Hoang; Arnob, Md Masud Parvez; Becker, Aaron T.; Wolfe, John C.; Hogan, Matthew K.; Horner, Philip J.; Shih, Wei-ChuanA multipoint, side-firing design enables an optical fiber to output light at multiple desired locations along the fiber body. This provides advantages over traditional end-to-end fibers, especially in applications requiring fiber bundles such as brain stimulation or remote sensing. This Letter demonstrates that continuous wave (CW) laser micro-ablation can controllably create conical-shaped cavities, or side windows, for outputting light. The dimensions of these cavities determine the amount of firing light and their firing angle. Experimental data show that a single side window on a 730 μm fiber can deliver more than 8% of the input light. This can be increased to more than 19% on a 65 μm fiber with side windows created using femtosecond laser ablation and chemical etching. Fine control of light distribution along an optical fiber is critical for various biomedical applications such as light-activated drug-release and optogenetics studies.Item Flexible, Self-Attaching Substrates for Extra-Neural Cuff Interfaces based on Shape-Shifting Polymers(2021-12) Randhawa, Navjot Singh; Wolfe, John C.; Gabbiani, Fabrizio; Karim, Alamgir; Shih, Wei-Chuan; Zagozdzon-Wosik, WandaElectrical recording and stimulation in the peripheral nervous system (PNS) is used to treat neurological disease, control neuro-prosthetic devices, and for fundamental studies in neuroscience. The study of natural neural networks is of particular interest for applications in the fields of machine learning, automation, self-driving cars, robotics, and unmanned aerial vehicles. Extra-neural cuffs, which wrap the nerve bundles with sensing/stimulating electrodes, are often preferred over penetrating probes because nerve damage is minimized. However, state-of-the-art extra-neural cuffs have many limitations including large size, a limited number of electrical contacts, a reliance on suturing for attachment to the nerves, low compliance and flexibility, and the inability to adjust to changes in nerve diameter during, for example, the flexing of joints. A serious problem for stiff cuffs is that they must be larger than the nerve to avoid compression damage. A gap between cuff and nerve then compromises spatial resolution and signal-to-noise ratio in recording cuffs and requires higher current pulses for stimulation. A gap can also serve as a pocket for growth of scar tissue which will further degrade communication between the electrode and the nerve, and can eventually lead to failure of the interface. This thesis presents fabrication and characterization of substrates for extra-neural cuff interfaces (ECI) that overcome the limitations outlined above. As a result, cuff interfaces made with these substrates will feature high longevity and resolution over a wide range of applications. These substrates are extremely thin (≤ 2 μm), have programmable diameters (over the range of 100-500 μm), and, being self-wrapping, they can securely hold nerves without suturing. Moreover, since suturing or other permanent attachment methods are unnecessary, the cuffs detach from the nerves when faced with extreme strain (e.g. due to the motion of motile limbs). Since the cuffs are so thin, they are highly compliant, and can accommodate increases in nerve diameter with little compression. The cuffs are also extremely resilient, retaining their diameter even after 100 open-close cycles. The ECI substrates have been targeted for recording neural signals on the descending contralateral movement detector (DCMD) neuron in the locust, which provides a direct insight to the mechanism of biophysical processing of the LGMD neuron. This will serve as the first step toward developing cuffs for clinical applications in humans. Shape-shifting phenomena of thin polymer films are used to create and characterize substrates for the ECI. We have explored two approaches to shift the shape of 2D films to a 3D structure. The first approach involves implanting the surface of 2 μm thick, monoaxially textured polymer films of polycarbonate (Makrofol and Lexan) and polyethylene terephthalate (Mylar) to a depth of ~ 0.6 μm with energetic helium ions. The implant causes chain scissioning and carbonizes the implanted region, thus, leading to shrinkage. This shrinkage causes global buckling of the resulting bilayer film. A careful tailoring of initial conditions of implantation method yields cuffs with diameters in 100-500 μm range. Unfortunately, with just implantation, the diameter of these cuffs is sensitive to ambient moisture, making them unreliable. For the second approach, in addition to helium ion implantation of 2 μm thick, monoaxially-textured polycarbonate film to ~ 0.6 μm depth, heating above its glass transition temperature (~ 300 F) is done. The heating shrinks the un-implanted layer (~ 1.4 μm thick) of polycarbonate in the textured direction. The difference in strain, thickness, and elastic modulus between the implanted and the un-implanted polycarbonate causes the bilayer to bend according to the Timoshenko model. Significantly, with this approach, radius of curvature is not affected by moisture; it is even impervious to immersion in phosphate buffered saline, which is widely used to simulate cerebro-spinal fluid. Bulge testing, tensile force measurements, surface energy determinations, and Raman spectroscopy were used to character the bilayer materials. Finally, some limitations of the current process are discussed and future work for fabricating functional extra-neural cuff interfaces is suggested.Item Fluidic Assisted Fabrication of Elastomer Optical Lenses Using Capillarity(2019-12) Kavishwar, Saket Vivek; Liu, Dong; Yang, Di; Shih, Wei-ChuanTraditional methods of optical glass-based lens fabrication require subtractive manufacturing, which leads to high loss of material and long cycle time. With polymeric lenses, however, additive manufacturing methods work very well and have advantages of shorter processing times, negligible material loss and reduced costs. Unfortunately, up to now, only small-sized polymeric lenses with plano-convex shape can be fabricated. The work described in this thesis proposes a fast, repeatable, and cost effective method of producing bi-convex and plano-convex polymeric lenses utilizing the capillarity effect at liquid-liquid interface. It was demonstrated that, by controlling the material properties, such as density, viscosity and interfacial tension, polymeric lenses with the desired magnifying power can be fabricated over a large size range. To explore the underlying dynamics of the multiphase interactions, numerical models were developed using the phase-field model. The dynamics of the lens forming process and the equilibrium shape of the polymeric lens can be captured by the numerical models. An analytical relationship between the lens volume, radius and thickness was also obtained by utilizing the Young-Laplace and force balance equations. The numerical and analytical predictions were validated by experimental results obtained using Polydimethylsiloxane (PDMS) as the lens material at the oil-water interface. It is expected that the quantitative understanding developed in this work will pave the way for future cost-effective manufacturing of polymeric optical lenses on a commercial scale.Item Game Theoretical Framework for Distributed Dynamic Control in Smart Grids(2013-12) Forouzandehmehr, Najmeh 1982-; Han, Zhu; Ogmen, Haluk; Mohsenian-Rad, Hamed; Khodaei, Amin; Shih, Wei-ChuanIn the emerging smart grids, production increasingly relies on a greater number of decentralized generation sites based on renewable energy sources. The variable nature of the new renewable energy sources will require a certain form of distributed energy storage, such as batteries, flywheels, compressed air and so on to help maintain supply security. Moreover, integration of demand response programs in conjunction with distrusted generation makes an economic and environmental advantage by altering end-users’ normal consumption patterns in response to changes in the electricity price. These new techniques change the way we consume and produce energy also enable the possibility to reduce the greenhouse effect and improve grid stability by optimizing energy streams. In order to accommodate these technologies, solid mathematical tools are essential to ensure robust operation of heterogeneous and distributed nature of smart grids. In this context, game theory could constitute a robust framework that can address relevant and timely open problems in the emerging smart grid networks. In this dissertation, three dynamic game-theoretical approaches are proposed for distributed control of generation and storage units and demand response applications in smart grid networks. We first study the competitive interactions between an autonomous pumpedstorage hydropower plant and a thermal power plant in order to optimize power generation and storage. Each type of power plant individually tries to maximize its own profit by adjusting its strategy: both types of plants can sell their power to the market; or alternatively, the thermal-power plant can sell its power at a fixed price to the pumped-storage hydropower plant by storing the energy in the reservoir. A stochastic differential game is formulated to characterize this competition. The solutions are derived using the stochastic Hamilton-Jacobi-Bellman equations. Based on the effect of real-time pricing on users’ daily demand profile, the simulation results demonstrate the properties of the proposed game and show how we can optimize consumers’ electricity cost in presence of time-varying prices. Second, we focus on controllable load types in energy-smart buildings that are associated with dynamic systems. In this regard, we propose a new demand response model based on a two-level differential game framework. At the beginning of each demand response interval, the price is decided by the upper level (aggregator, utility, or market) given the total demand of lower level users. Given the price from the upper level, the electricity usage of air conditioning unit and the battery storage charging/discharging schedules are controlled for each player (buildings that are equipped with automated load control systems and local renewable generators), in order to minimize the user’s total electricity cost. The optimal user strategies are derived, and we also show that the proposed game can converge to a feedback Nash equilibrium. Finally, the problem of distributed control of the heating, ventilation and air conditioning (HVAC) system for multiple zones in an energy-smart building is addressed. This analysis is based on the idea of satisfaction equilibrium, where the players are exclusively interested in the satisfaction of their individual constraints instead of individual performance optimization. This configuration enables a HVAC unit as a player to make stochastically stable decisions with limited information from the rest of players. To achieve satisfaction equilibrium, a learning dynamics based on trialand- error learning is proposed. In particular, it is shown that this algorithm reaches stochastically stable states that are equilibria and maximizers of the global welfare of the corresponding game.Item High-Magnification Digital Staining of FTIR Spectroscopic Images(2017-12) Daeinejad, Seyeddavar; Mayerich, David; Shih, Wei-Chuan; Eriksen, Jason; Nguyen, Hien VanHistopathology, the examination of molecular and microscopic structures, is essential in tissue analysis and disease diagnosis. It currently relies on the use of dyes and stains to label the morphology and the chemical composition of tissue samples. It relies heavily on human interpretation of the tissue and the chemical staining process has several limitations in histopathologic examinations. FTIR spectroscopic imaging has seen groundbreaking success in the characterization of tissue, but has yet to provide practical pathological examination of biopsies. In an attempt to build a bridge between modern spectroscopic imaging techniques and current clinical research, digital staining aims to make a rapid and quantitative solution available by providing additional molecular and morphological information for pathology. In this work, we develop digital staining techniques that can be applied to high-magnification samples collected using Fourier-transform infrared (FTIR) and discrete-frequency infrared (DFIR) images.