Polarization imaging and polarization microscopy is of great interest in industrial inspection, defense, biomedical and clinical research, food safety, etc. An ideal polarization imaging system suitable for versatile applications should be full-Stokes, compact, broadband, fast, and highly accurate within a…
Polarization imaging and polarization microscopy is of great interest in industrial inspection, defense, biomedical and clinical research, food safety, etc. An ideal polarization imaging system suitable for versatile applications should be full-Stokes, compact, broadband, fast, and highly accurate within a large operation angle. However, such a polarization imaging system remains elusive among state-of-the-art technology. Recently, flat optics based on metasurfaces have been explored for polarization detection and imaging. Compared with state-of-art, metasurface-based solutions have the advantages of compactness, great design flexibility, and feasibility for on-chip integration. This dissertation reports a dual wavelength (630 to 670nm and 480nm to 520nm) chiral metasurfaces featured with sub-wavelength dimension, extinction ratio over 10 across a broad operation bandwidth (175nm) and efficiency over 60%, which can be used for detection and generation of circular polarization (Chapter 2).
This dissertation then reports a chip-integrated full-Stokes polarimetric Complementary metal–oxide–semiconductor (CMOS) imaging sensor based on metasurface polarization filter arrays (MPFA) mentioned above. The sensor has high measurement accuracy of polarization states with an angle of view up to 40°. Calibration and characterization of the device are demonstrated, whereby high polarization states measurement accuracy (measurement error <4%) at incidence angle up to ±20° and full Stokes polarization images of polarized objects are shown. (Chapter 3).
A scalable fabrication approach based on nano imprint lithography is demonstrated, with improved fabrication efficiency, lower cost, and higher optical performance up to 10 times compared to EBL process. (Chapter 4).
Several polarization imaging applications including a dual-camera full-Stokes underwater polarization navigation system are discussed. Polarization mapping under clear sky and clear water is demonstrated for proof concept. Enhancing contrast of objects through turbid water and polarization images of silver dendrites are also discussed (Chapter 5).
Though distinctive in its advantages in rich polarization information, most existing Mueller matrix microscope (MMM) operate at single mode, narrow bandwidth with bulky components. This dissertation reports a compact, dual wavelength, dual mode MMM with satisfactory measurement accuracy (Mueller matrix (MM) measurement error≤ 2.1%) using polarimetric imaging sensor mentioned previously, MM imaging of photonic structures, bio-tissues, etc are demonstrated for proof of concept (Chapter 6).
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The development of biosensing platforms not only has an immediate lifesaving effect but also has a significant socio-economic impact. In this dissertation, three very important biomarkers with immense importance were chosen for further investigation, reducing the technological gap and improving…
The development of biosensing platforms not only has an immediate lifesaving effect but also has a significant socio-economic impact. In this dissertation, three very important biomarkers with immense importance were chosen for further investigation, reducing the technological gap and improving their sensing platform.Firstly, gold nanoparticles (AuNP) aggregation and sedimentation-based assays were developed for the sensitive, specific, and rapid detection of Ebola virus secreted glycoprotein (sGP)and severe acute respiratory syndrome coronavirus 2 (SARS-COV2) receptor-binding domain (RBD) antigens. An extensive study was done to develop a complete assay workflow from critical nanobody generation to optimization of AuNP size for rapid detection. A rapid portable electronic reader costing (<$5, <100 cm3), and digital data output was developed. Together with the developed workflow, this portable electronic reader showed a high sensitivity (limit of detection of ~10 pg/mL, or 0.13 pM for sGP and ~40 pg/mL, or ~1.3 pM for RBD in diluted human serum), a high specificity, a large dynamic range (~7 logs), and accelerated readout within minutes. Secondly, A general framework was established for small molecule detection using plasmonic metal nanoparticles through wide-ranging investigation and optimization of assay parameters with demonstrated detection of Cannabidiol (CBD). An unfiltered assay suitable for personalized dosage monitoring was developed and demonstrated. A portable electronic reader demonstrated optoelectronic detection of CBD with a limit of detection (LOD) of <100 pM in urine and saliva, a large dynamic range (5 logs), and a high specificity that differentiates closely related Tetrahydrocannabinol (THC). Finally, with careful biomolecular design and expansion of the portable reader to a dual-wavelength detector the classification of antibodies based on their affinity to SARS-COV2 RBD and their ability to neutralize the RBD from binding to the human Angiotensin-Converting Enzyme 2 (ACE2) was demonstrated with the capability to detect antibody concentration as low as 1 pM and observed neutralization starting as low as 10 pM with different viral load and variant. This portable, low-cost, and versatile readout system holds great promise for rapid, digital, and portable data collection in the field of biosensing.
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This work is aimed at detecting and assessing the performance of colorimetricgold nanoparticle (AuNP) based biosensors, designed to inspect 17-beta-estradiol (E2), SARS-Cov-2 (RBD), and Ebola virus secreted glycoprotein (sGP) with samples at different concentration ranges. The biosensors are able to…
This work is aimed at detecting and assessing the performance of colorimetricgold nanoparticle (AuNP) based biosensors, designed to inspect 17-beta-estradiol (E2), SARS-Cov-2 (RBD), and Ebola virus secreted glycoprotein (sGP) with samples at different concentration ranges. The biosensors are able to provide a colorimetric readout, that enables the detection signal to be transmitted via a simple glance, which renders these biosensors cheap and rapid therefore enabling for their implementation into point of care (POC) devices for diagnostic testing in harsh /rural environments, where there is a lack of machinery or trained staff to carry out the diagnosis experiments. Or their implementation into POC devices in medical areas for clinical diagnosis. The intent of this research is to detect the targets of interest such as E2 at a lower limit of detection (LOD), and such as RBD using a novel biosensor design. The verification of the colorimetric results is done via transmission spectra recordings and a compilation of the extinction, where an S-curve relative to the detection concentrations can be seen. This research displays, the fabrication of numerous biosensors and using them in detection experiments to hypothesize the performance of detection using target samples. Additionally, this color change is quantifiable by transmission spectrum recordings to compile the data and calculate the extinction S curve. With the least extinction values pertaining to the highest concentration of detection and the highest extinction values is at the lowest concentration of detection.
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Patterning technologies for micro/nano-structures have been essentially used in a variety of discipline research areas, including electronics, optics, material science, and biotechnology. Therefore their importance has dramatically increased over the past decades. This dissertation presents various advanced patterning processes utilizing…
Patterning technologies for micro/nano-structures have been essentially used in a variety of discipline research areas, including electronics, optics, material science, and biotechnology. Therefore their importance has dramatically increased over the past decades. This dissertation presents various advanced patterning processes utilizing cross-discipline technologies, e.g., photochemical deposition, transfer printing (TP), and nanoimprint lithography (NIL), to demonstrate inexpensive, high throughput, and scalable manufacturing for advanced optical applications.
The polymer-assisted photochemical deposition (PPD) method is employed in the form of additive manufacturing (AM) to print ultra-thin (< 5 nm) and continuous film in micro-scaled (> 6.5 μm) resolution. The PPD film acts as a lossy material in the Fabry-Pérot cavity structures and generates vivid colored images with a micro-scaled resolution by inducing large modulation of reflectance. This PPD-based structural color printing performs without photolithography and vacuum deposition in ambient and room-temperature conditions, which enables an accessible and inexpensive process (Chapter 1).
In the TP process, germanium (Ge) is used as the nucleation layer of noble metallic thin films to prevent structural distortion and improve surface morphology. The developed Ge-assisted transfer printing (GTP) demonstrates its feasibility transferring sub-100 nm features with up to 50 nm thickness in a centimeter scale. The GTP is also capable of transferring arbitrary metallic nano-apertures with minimal pattern distortion, providing relatively less expensive, simpler, and scalable manufacturing (Chapter 2).
NIL is employed to fabricate the double-layered chiral metasurface for polarimetric imaging applications. The developed NIL process provides multi-functionalities with a single NIL, i.e., spacing layer, planarized surface, and formation of dielectric gratings, respectively, which significantly reduces fabrication processing time and potential cost by eliminating several steps in the conventional fabrication process. During the integration of two metasurfaces, the Moiré fringe based alignment method is employed to accomplish the alignment accuracy of less than 200 nm in both x- and y-directions, which is superior to conventional photolithography. The dramatically improved optical performance, e.g., highly improved circular polarization extinction ratio (CPER), is also achieved with the developed NIL process (Chapter 3).
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The stability of cheerleading stunts is crucial to athlete safety and team success. Consistency in stunt technique contributes to success in stunting skills, giving a team the tools to win competitions. Increased stunt technique reduces the chances of falls and…
The stability of cheerleading stunts is crucial to athlete safety and team success. Consistency in stunt technique contributes to success in stunting skills, giving a team the tools to win competitions. Increased stunt technique reduces the chances of falls and the severity of those falls. Proper technique also prevents injuries caused by improper positions that place pressure on the lower back and shoulders. Bases must maintain strong technique with proper lines of support in order to maximize stunt stability. Through exploration of the EmbeddedML system, involving a neural network implemented using a SensorTile, cheerleading motions can be successfully classified. Using this system, it is possible to identify motions that result in both weak and injurious positions almost instantly. By alerting athletes to these incorrect motions, improper stunt technique can be corrected quickly and without the involvement of a coach. This automated technique correction would be incredibly beneficial to the sport of competitive cheerleading
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This dissertation aims to study the electron and spin transport, scattering in two dimensional pseudospin-1 lattice systems, hybrid systems of topological insulator and magnetic insulators, and molecule chain systems. For pseudospin-1 systems, the energy band consists of a pair of…
This dissertation aims to study the electron and spin transport, scattering in two dimensional pseudospin-1 lattice systems, hybrid systems of topological insulator and magnetic insulators, and molecule chain systems. For pseudospin-1 systems, the energy band consists of a pair of Dirac cones and a flat band through the connecting point of the cones. First, contrary to the conditional wisdom that flatband can localize electrons, I find that in a non-equilibrium situation where a constant electric field is suddenly switched on, the flat band can enhance the resulting current in both the linear and nonlinear response regimes compared to spin-1/2 system. Second, in the setup of massive pseudospin-1 electron scattering over a gate potential scatterer, I discover the large resonant skew scattering called super skew scattering, which does not arise in the corresponding spin-1/2 system and massless pseudospin-1 system. Third, by applying an appropriate gate voltage to generate a cavity in an alpha-T3 lattice, I find the exponential decay of the quasiparticles from a chaotic cavity, with a one-to-one correspondence between the exponential decay rate and the Berry phase for the entire family of alpha-T3 materials. Based on the hybrid system of a ferromagnetic insulator on top of a topological insulator, I first investigate the magnetization dynamics of a pair of ferromagnetic insulators deposited on the surface of a topological insulator. The spin polarized current on the surface of topological insulator can affect the magnetization of the two ferromagnetic insulators through proximity effect, which in turn modulates the electron transport, giving rise to the robust phase locking between the two magnetization dynamics. Second, by putting a skyrmion structure on top of a topological insulator, I find robust electron skew scattering against skyrmion structure even with deformation, due to the emergence of resonant modes. The chirality of molecule can lead to spin polarized transport due to the spin orbit interaction. I investigate spin transport through a chiral polyacetylene molecule and uncover the emergence of spin Fano resonances as a manifestation of the chiral induced spin selectivity effect.
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Biodiversity has been declining during the last decades due to habitat loss, landscape deterioration, environmental change, and human-related activities. In addition to its economic and cultural value, biodiversity plays an important role in keeping an environment’s ecosystem in balance. Disrupting…
Biodiversity has been declining during the last decades due to habitat loss, landscape deterioration, environmental change, and human-related activities. In addition to its economic and cultural value, biodiversity plays an important role in keeping an environment’s ecosystem in balance. Disrupting such processes can reduce the provision of natural resources such as food and water, which in turn yields a direct threat to human health. Protecting and restoring natural areas is fundamental to preserve biodiversity and to mitigate the effects of ongoing environmental change. Unfortunately, it is impossible to protect every critical area due to resource limitations, requiring the use of advanced decision tools for the design of conservation plans. This dissertation studies three problems on the design of wildlife corridors and reserves that include patch-specific conservation decisions under spatial, operational, ecological, and biological requirements. In addition to the ecological impact of each problem’s solution, this dissertation contributes a set of formulations, valid inequalities, and pre-processing and solution algorithms for optimization problems with spatial requirements. The first problem is a utility-based corridor design problem to connect fragmented habitats, where each patch has a utility value reflecting its quality. The corridor must satisfy geometry requirements such as a connectivity and minimum width. We propose a mix-integer programming (MIP) model to maximize the total utility of the corridor under the given geometry requirements as well as a budget constraint to reflect the acquisition (or restoration) cost of the selected patches. To overcome the computational difficulty when solving large-scale instances, we develop multiple acceleration techniques, including a brand-and-cut algorithm enhanced with problem-specific valid inequalities and a bound-improving heuristic triggered at each integer node in the branch-and-bound exploration. We test the proposed model and solution algorithm using large-scale fabricated instances and a real case study for the design of an ecological corridor for the Florida Panther. Our modeling framework is able to solve instances of up to 1500 patches within 2 hours to optimality or with a small optimality gap. The second problem introduces the species movement across the fragmented landscape into the corridor design problem. The premise is that dispersal dynamics, if available, must inform the design to account for the corridor’s usage by the species. To this end, we propose a spatial discrete-time absorbing Markov chain (DTMC) approach to represent species dispersal and develop short- and long-term landscape usage metrics. We explore two different types of design problems: open and closed corridors. An open corridor is a sequence of landscape patches used by the species to disperse out of a habitat. For this case, we devise a dynamic programming algorithm that implicitly enumerates possible corridors and finds that of maximum probability. The second problem is to find a closed corridor of maximum probability that connects two fragmented habitats. To solve this problem variant, we extended the framework from the utility-based corridor design problem by blending the recursive Markov chain equations with a network flow nonlinear formulation. The third problem leverages on the DTMC approach to explore a reserve design problem with spatial requirements like connectivity and compactness. We approximate the compactness using the concept of maximum reserve diameter, i.e., the largest distance allowed between two patch in the reserve. To solve this problem, we devise a two-stage approach that balances the trade-off between reserve usage probability and compactness. The first stage's problem is to detect a subset of patches of maximum usage probability, while the second stage's problem imposes the geometry requirements on the optimal solution obtained from the first stage. To overcome the computational difficulty of large-scale landscapes, we develop tailored solution algorithms, including a warm-up heuristic to initialize the branch-and-bound exploration, problem-specific valid inequalities, and a decomposition strategy that sequentially solves smaller problems on landscape partitions.
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Quantifying molecular interactions is critical to the understanding of many biological processes and drug screening. To date, various detection techniques have been developed to determine the binding kinetics. However, because most of the mainstream detection technologies detect signals that scale…
Quantifying molecular interactions is critical to the understanding of many biological processes and drug screening. To date, various detection techniques have been developed to determine the binding kinetics. However, because most of the mainstream detection technologies detect signals that scale with the mass of ligands bond to the sensor surface, it is still challenging to quantify the binding kinetics of small molecules. To address this problem, two different detection technologies, charge-sensitive optical detection (CSOD) and critical angle reflection (CAR), are developed for label-free detection of molecular interactions with the ability to detect a wide range of molecules including small molecules. In particular, CSOD technique detects the charge rather than the mass of a molecule with an optical fiber. However, the effective charge of a molecule decreases with the buffer ionic strength. For this reason, the previous CSOD works with diluted buffers, which could affect the measured molecular binding kinetics. Here a technique capable of detecting molecular binding kinetics in normal ionic strength buffers is presented. An H-shaped sample well was developed to overcome this problem. With this new design, the binding kinetics between G-protein-coupled receptors (GPCRs) and their small molecule ligands were measured in normal buffer. To further improve the signal-to-noise ratio of CSOD and move it toward high-throughput detection, CSOD was implemented with a quadrant-cell detector to achieve detection in higher frequency range and decrease low-frequency noise.This improved CSOD technique is capable for direct quantification of binding kinetics of phage-displayed peptides to their target protein using the whole phages. CAR imaging can be performed on surface plasmon resonance (SPR) imaging setups. It was shown that CAR is capable of measuring molecular interactions including proteins, nucleic acids and cell-based detections. In addition, it was shown that CAR can detect small molecule bindings and intracellular signals beyond SPR sensing limit. CAR exhibits several distinct characteristics over SPR, including tunable sensitivity and dynamic range, deeper vertical sensing range, and fluorescence compatibility. CAR is anticipated to have the ability to expand SPR capability in small molecule detection, whole cell-based detection, simultaneous fluorescence imaging, and broader conjugation chemistry.
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Design and development of optical sensors for the detection of specific targets, e.g., ions, molecules, proteins, light polarizations, is one of the most essential research topics in the field of nanophotonics that paves the way for significant technological progressions in…
Design and development of optical sensors for the detection of specific targets, e.g., ions, molecules, proteins, light polarizations, is one of the most essential research topics in the field of nanophotonics that paves the way for significant technological progressions in chemical and biomarker detections, polarimetric imaging and other sensing related applications. In this dissertation, three designs of optical sensors based on plasmonic and dielectric nanostructures are thoroughly studied for the applications in chemicals, biomarkers and light polarization detection. Firstly, a plasmonic nanoantenna structure, which is composed of complementary anisotropic nanobars and nanoapertures featuring strong localized electric field enhancement at nanogap region, demonstrates both high sensitivity refractometric detection and specific infrared fingerprint detection for chemical sensing. Specifically, the sensor can probe monolayer thin octadecanethiol with a large resonance shift of 136 nm and all four characteristic infrared fingerprints detected. Secondly, a bio-inspired double-layered metasurface structure, which is made of dielectric nanoantenna and plasmonic nanogratings, mediates strong optical chirality and enables the selection of circularly polarized light handedness (extinction ratio ≥ 35) with high transmission efficiency (≥ 80%). The structure can be further integrated on-chip with linear polarizers for highly precise full-Stokes polarimetric detection with minimum transmission loss. Lastly, a gold nanoparticle based colorimetric assay is designed for high sensitivity, specificity and rapid detection of infectious diseases related biomarkers. The complete design workflows from critical reagents productions, rapid detection protocol to assay characterizations are extensively studied. Detection of Ebola virus disease biomarker, secreted glycoprotein, within 20 minutes are experimentally demonstrated with limit of detection down to ~40 pM and a broad detection range from 10 pM to 1 µM.
The designs of the three sensors propose novel and versatile design concepts for the development of sensing devices in the detection of chemicals, biomarkers and light polarization. The efforts in the fundamental theoretical analysis and experimental demonstrations are expected to provide valuable contents to the optical sensor researches and to potentially inspire new sensor designs for broad sensing applications in the future.
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Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an…
Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF–TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.
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