R-3 Repository :: Browsing by Author "Kelly, Kevin F."

Browsing by Author "Kelly, Kevin F."

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A hyperspectral projector for simultaneous 3D spatial and hyperspectral imaging via structured illumination
(Optical Society of America, 2020) Xu, Yibo; Giljum, Anthony; Kelly, Kevin F.
Both 3D imaging and hyperspectral imaging provide important information of the scene and combining them is beneficial in helping us perceive and understand real-world structures. Previous hyperspectral 3D imaging systems typically require a hyperspectral imaging system as the detector suffers from complicated hardware design, high cost, and high acquisition and reconstruction time. Here, we report a low-cost, high-frame rate, simple-design, and compact hyperspectral stripe projector (HSP) system based on a single digital micro-mirror device, capable of producing hyperspectral patterns where each row of pixels has an independently programmable spectrum. We demonstrate two example applications using the HSP via hyperspectral structured illumination: hyperspectral 3D surface imaging and spectrum-dependent hyperspectral compressive imaging of volume density of participating medium. The hyperspectral patterns simultaneously encode the 3D spatial and spectral information of the target, requiring only a grayscale sensor as the detector. The reported HSP and its applications provide a solution for combining structured illumination techniques with hyperspectral imaging in a simple, efficient, and low-cost manner. The work presented here represents a novel structured illumination technique that provides the basis and inspiration of future variations of hardware systems and software encoding schemes.
A Phantom Study of In-beam PET Imaging for Proton Beam Range Verification
(2013-12-17) Lou, Kai; Clark, John W., Jr.; Kelly, Kevin F.; Jacot, Jeffrey G.; Shao, Yiping
In-beam PET imaging is an advanced image-based method to verify the proton beam range for proton therapy by measuring proton-induced positron activity distribution and activity range. This study investigates the feasibility, accuracy and precision of the activity range measurement with a high-performance compact PET prototype system for in-beam PET imaging. An experiment with a homogeneous PMMA phantom and several Monte Carlo simulation studies are conducted. The results have shown that the prototype PET can provide reasonably good images for the activity range measurement even with low count statistics; the accuracy of activity range measurement reaches sub-millimeter; 11C is the most dominating positron emission isotope contributing to the overall positron activity; the image quality and the precision of activity range measurement depend on the count statistics, and high count statistics leads to improved image quality and precision. Although the study is preliminary with simple system set-ups, it does provide interesting and important results which should lay the basis leading to future clinically relevant investigations.
Apparatus and method for compressive imaging and sensing through multiplexed modulation
(2015-09-01) Kelly, Kevin F.; Baraniuk, Richard G.; Woods, Gary; Sun, Ting; Turner, Matthew; Rice University; United States Patent and Trademark Office
Compressive imaging apparatus employing multiple modulators in various optical schemes to generate the modulation patterns before the signal is recorded at a detector. The compressive imaging apparatus is equally valid when applying compressive imaging to structured light embodiments where the placement is shifted from the acquisition path between the subject and the detector into the illumination path between the source and the subject to be imaged.
Apparatus and method for compressive imaging and sensing through multiplexed modulation via spinning disks
(2016-12-13) Kelly, Kevin F.; Baraniuk, Richard G.; Woods, Gary; Sun, Ting; Turner, Matthew; Rice University; United States Patent and Trademark Office
Compressive imaging apparatus employing multiple modulators in various optical schemes to generate the modulation patterns before the signal is recorded at a detector. The compressive imaging apparatus is equally valid when applying compressive imaging to structured light embodiments where the placement is shifted from the acquisition path between the subject and the detector into the illumination path between the source and the subject to be imaged.
Atomic-level investigation of fluorinated single-wall carbon nanotubes
(2005) Takhar, Dharmpal; Kelly, Kevin F.
There is a great deal of interest in the functionalization, in particular fluorination, of single-wall carbon nanotubes (SWNTs) for the purposes of solvation and subsequent chemical reaction. Towards this end, this thesis reports the investigation of fluorinated SWNTs (fluorotubes) performed by scanning tunneling microscopy (STM). This research was performed for various compositions of fluorinated nanotubes. In addition, the atomic-scale fluorine coverage on the fluorotubes with composition was observed as a function of annealing temperature. Upon heating of the fluorotubes, we observe the subsequent desorption of the fluorine initiated around 240°C. At higher temperatures all the fluorine desorbs from the tubes revealing a few "defects" still remaining. Further heating leads to cutting of the fluorotubes which we believe is initiated at these defect locations. Through these studies we gain important information on the local chemistry as well as the electronic structure of the functionalized carbon nanotubes.
Atomic-scale investigation of polydiacetylene nanowires by scanning tunneling microscopy and spectroscopy
(2006) Giridharagopal, Rajiv; Kelly, Kevin F.
Nanowires comprised of polydiacetylene, a conjugated polymer, have been analyzed at the nanoscale using scanning tunneling microscopy (STM) and spectroscopy. STM analysis shows that these nanowires exhibit unique electronic behavior due to the different substrate electrode materials used, particularly graphite and molybdenum disulfide. The change in charge transfer behavior is evidence of the importance of polymer-electrode interactions. Nanowires are also shown to randomly desorb due to an interaction with the STM tip. A single disruption often results in the entire nanowire desorbing, and the underlying monolayer is reordered within milliseconds. Additionally, spectroscopic data has been acquired using a novel technique called alternating current STM (ACSTM). ACSTM allows for the acquisition of differential capacitance information. Analysis of the nanowires yields a peak in differential capacitance, as is typical of metal/insulator/semiconductor structures. The ACSTM is sensitive to both carrier concentration and dopant type, making it ideal for future metrological applications.
Characterization of functionalized carbon nanotubes and graphite
(2008) Kang, JungHo; Kelly, Kevin F.
Graphene and carbon nanotubes have drawn much attention in the last decade, and functionalization of these materials is considered a great technique for manipulating them. In this project, we mainly investigated functionalized double-wall carbon nanotube and functionalized graphite. Due to the unique physical structure of double-wall carbon nanotubes (DWNTs), the outer tube can be chemically functionalized while the inner tube is left in pristine condition. The diameter of bare DWNTs is around 2-3 nm as measured by scanning tunneling microscopy (STM), but fluorinated DWNTs possess much larger diameters, from 3-10 nm, due to a stronger electronic interaction. In addition to imaging the as prepared material, the material was imaged after annealing at temperatures up to 1000 K. Due to the defluorination, the diameter is decreased to that of the initial bare DWNTs and atomic resolution of the lattice was recovered. In addition, it was possible to observe the initial and final structures on the same nanotubes and the evolution of their associated defect structures. Lastly, Raman spectroscopy was employed to confirm the defluorination by revealing the recovery of the radial breathing mode which disappeared upon fluorination. Also, we investigate the epoxidation mechanism on graphite surfaces with STM and Raman spectroscopy, and our results indicate that the functionalzation occurs on the edges, not on the basal plane as reported previously.
Charge Transport and Transfer at the Nanoscale Between Metals and Novel Conjugated Materials
(2012-09-05) Worne, Jeffrey; Natelson, Douglas; Kelly, Kevin F.; Mittleman, Daniel M.
Abstract Organic semiconductors (OSCs) and graphene are two classes of conjugated materials that hold promise to create flexible electronic displays, high speed transistors, and low-cost solar cells. Crucial to understanding the behavior of these materials is understanding the effects metallic contacts have on the local charge environment. Additionally, characterizing the charge carrier transport behavior within these materials sheds light on the physical mechanisms behind transport. The first part of this thesis examines the origin of the low-temperature, high electric field transport behavior of OSCs. Two chemically distinct OSCs are used, poly-3(hexylthiophene) (P3HT) and 6,13- bis(triisopropyl-silylethynyl) (TIPS) pentacene. Several models explaining the low-temperature behavior are presented, with one using the Tomonaga-Luttinger liquid (TLL) insulator-to-metal transition model and one using a field-emission hopping model. While the TLL model is only valid for 1-dimensional systems, it is shown to work for both P3HT (1D) and TIPS-pentacene (2D), suggesting the TLL model is not an appropriate description of these systems. Instead, a cross-over from thermally-activated hopping to field-emission hopping is shown to explain the data well. The second part of this thesis focuses on the interaction between gold and platinum contacts and graphene using suspended graphene over sub-100 nanometer channels. Contacts to graphene can strongly dominate charge transport and mobility as well as significantly modify the charge environment local to the contacts. Platinum electrodes are discovered to be strong dopants to graphene at short length scales while gold electrodes do not have the same effect. By increasing the separation distance between the electrodes, this discrepancy is shown to disappear, suggesting an upper limit on charge diffusion from the contacts. Finally, this thesis will discuss a novel technique to observe the high-frequency behavior in OSCs using two microwave sources and an organic transistor as a mixer. A theoretical model motivating this technique is presented which suggests the possibility of retrieving gigahertz charge transport phenomena at kilohertz detection frequencies. The current state of the project is presented and discrepancies between devices made with gold and platinum electrodes measured in the GHz regime are discussed.
Compressed Sensing for Imaging Applications
(2008) Takhar, Dharmpal; Kelly, Kevin F.; Baraniuk, Richard G.; Yin, Wotao
Compressed sensing is a new sampling theory which allows reconstructing signals using sub-Nyquist measurements. This can significantly reduce the computation required for both image and video whether during acquisition or encoding, especially at the sensor. Compressed sensing works on the assumption of sparsity of the signal in some known domain, which is incoherent with the measurement domain. We exploit this technique to build a single pixel camera using an optical modulator and a single photosensor. Random projections of the signal (image) are applied to the optical modulator, which has a random matrix displayed on it corresponding to the measurement domain (random noise). This random projected signal is focused and summed at the photosensor and will be later used for reconstructing the signal. In this scheme, a tradeoff between the spatial extent of sampling array and a sequential sampling over time with a single detector is performed. In addition to the single sensor method, we will also demonstrate a new design which allows compressive im
Compressed Sensing Spectroscopy and Dynamic-Rate Neural Network Classification
(2021-10-07) Liu, Weidi; Kelly, Kevin F.
Compressive sensing (CS) is an approach for efficient signal acquisition based on the compressibility of the data and allowing the reconstruction signals below the Shannon-Nyquist sampling rate. Besides imaging, compressive sensing can be exploited in spectrometer design. Here we have constructed and compared a broadband, high resolution Echelle spectrometer against a potentially higher resolution, narrower band Sagnac Fourier spectrometer that also has larger signal intensity. The goal of each is a field-deployable Raman gas isotope system. The initial demonstration will have hardware resolution and algorithms specific to oxygen isotope identification. The end goal is also detection and recognition directly on the compressive measurements without needing to first reconstruct the entire spectrum. Towards that end, we have also combined the mathematics of manifold secants in multiple network structures to construct a detection and classification algorithm useful for spectra, as well as images. Combining this with dynamic-rate training scheme, we reach higher classification accuracy and need only a few measurement rates for training for the chosen dataset with a single neural network, rather than training a unique neural network for each rate.
Compressive Hyperspectral Imaging and Machine Vision
(2019-11-21) Xu, Yibo; Kelly, Kevin F.
Hyperspectral imaging is a challenging task given the high dimensionality of data and the limitations of conventional sensing scheme and detector design. Yet, it has great potential in studying optical phenomena in both science and engineering, and in both microscopic and macroscopic systems. Simultaneously, machine vision is an important field with a wide range of real-world applications. There has been constant effort to improve the accuracy and efficiency of machine vision implementations. The field of compressive sensing and its ability to exploit the inherent sparsity of a majority of natural images have the potential to make a tremendous impact on both of these fields. As such, the first part of this thesis describes the design and implementation of a compressive hyperspectral microscope that can capture and analyze different properties of metallic nanoparticles, fluorescent microspheres and two-dimensional materials. In relation to macroscale imaging, a hyperspectral projector system is developed and implemented as discussed in the middle portion of this thesis. It enhances conventional structured illumination methods by incorporating hyperspectral compressive measurements. Lastly, a general and efficient dynamic-rate training scheme for neural networks is developed and implemented that specifically exploits compressive measurements. The approach is capable of performing classification over a range of measurement rates directly on compressive measurements acquired by a single-pixel camera architecture bypassing image reconstruction. Since the input layer of the network is designed to couple with a single sensor, this approach is also compatible with a compressive hyperspectral imager. Overall, the results in this thesis presents many novel ways in which compressive sensing can greatly benefit both hyperspectral imaging and machine vision tasks.
Compressive Hyperspectral Microscopy of Scattering and Fluorescence of Nanoparticles
(American Chemical Society, 2022) Xu, Yibo; Lu, Liyang; Giljum, Anthony; Payne, Courtney M.; Hafner, Jason H.; Ringe, Emilie; Kelly, Kevin F.
Hyperspectral imaging in optical microscopy is of importance in the study of various submicron physical and chemical phenomena. However, its practical application is still challenging because the additional spectral dimension increases the number of sampling points to be independently measured compared to two-dimensional (2D) imaging. Here, we present a hyperspectral microscopy system through passive illumination approach based on compressive sensing (CS) using a spectrometer with a one-dimensional (1D) detector array and a digital micromirror device (DMD). The illumination is patterned after the sample rather than on it, making this technique compatible with both dark-field and bright-field imaging. The DMD diffraction issue resulting from this approach has been overcome by a novel striped DMD pattern modulation method. In addition, a split pattern method is developed for increasing the spatial resolution when employing the DMD pattern modulation. The efficacy of the system is demonstrated on nanoparticles using two model systems: extended plasmonic metal nanostructures and fluorescent microspheres. The compressive hyperspectral microscopic system provides a fast, high dynamic range, and enhanced signal-to-noise ratio (SNR) platform that yields a powerful and low-cost spectral analytical system to probe the optical properties of a myriad of nanomaterial systems. The system can also be extended to wavelengths beyond the visible spectrum with greatly reduced expense compared to other approaches that use 2D array detectors.
Compressive Hyperspectral Video Detection and Imaging
(2017-04-20) Lu, Liyang; Kelly, Kevin F.
Hyperspectral video imaging remains a challenging task given the high dimensionality of the datasets and the limited imaging spatio-spectral-temporal tradeoffs via current methods. Yet, it has great potential in studying a variety of dynamic optical phenomena, both in microscopic and macroscopic systems. The first part of this thesis describes the design and implementation of spatially compressive hyperspectral imaging for dark-field and broad-band sum-frequency generation microscopy in order to capture and analyze different nanomaterial properties. Next, a compressive classification method using secant patterns is designed to perform task-aware compressive sensing. It achieves fast and efficient classification based on sampling but not full reconstruction using single-pixel camera hardware. Lastly, a novel compressive imaging system, the single-doxel imager (SDI), is demonstrated for four dimensional hyperspectral video imaging. It is uniquely based on a single light modulator and a single detector. By performing optical spatial and spectral modulations simultaneously with a set of designed spatio-spectral modulation patterns, it can encode hyperspectral information into a highly compressed sequence of measurements. Along with the novel optical design, a new compressive imaging reconstruction algorithm is also implemented, which is able to exploit the inherent redundancy in the 4D temporal-spatio-spectral datacube. Using this system, single-pixel hyperspectral video imaging that achieves a compression ratio of 900 to 1 is demonstrated.
Compressive Sensing and Imaging Applications
(2012) Sun, Ting; Kelly, Kevin F.
Compressive sensing (CS) is a new sampling theory which allows reconstructing signals using sub-Nyquist measurements. It states that a signal can be recovered exactly from randomly undersampled data points if the signal exhibits sparsity in some transform domain (wavelet, Fourier, etc). Instead of measuring it uniformly in a local scheme, signal is correlated with a series of sensing waveforms. These waveforms are so called sensing matrix or measurement matrix. Every measurement is a linear combination of randomly picked signal components. By applying a nonlinear convex optimization algorithm, the original can be recovered. Therefore, signal acquisition and compression are realized simultaneously and the amount of information to be processed is considerably reduced. Due to its unique sensing and reconstruction mechanism, CS creates a new situation in signal acquisition hardware design as well as software development, to handle the increasing pressure on imaging sensors for sensing modalities beyond visible (ultraviolet, infrared, terahertz etc.) and algorithms to accommodate demands for higher-dimensional datasets (hyperspectral or video data cubes). The combination of CS with traditional optical imaging extends the capabilities and also improves the performance of existing equipments and systems. Our research work is focused on the direct application of compressive sensing for imaging in both 2D and 3D cases, such as infrared imaging, hyperspectral imaging and sum frequency generation microscopy. Data acquisition and compression are combined into one step. The computational complexity is passed to the receiving end, which always contains sufficient computer processing power. The sensing stage requirement is pushed to the simplest and cheapest level. In short, simple optical engine structure, robust measuring method and high speed acquisition make compressive sensing-based imaging system a strong competitor to the traditional one. These applications have and will benefit our lives in a deeper and wider way.
Developing Compressive Sensing in Electron Microscopy and Gas Phase Spectroscopy
(2023-04-21) Liu, Weidi; Kelly, Kevin F.
Compressive sensing is a technology that allows the original signal to be reconstructed with far fewer multiplexed measurements than the Shannon-Nyquist sampling rate. Compared to conventional methods, it can provide a comparable quality result with a much lower sampling time, while offering the advantage of higher signal-to-noise ratio. The first part of the work focuses on research using manifold secant patterns for classification in the field of Cryogenic electron microscopy (cryo-EM). In certain scenarios, the main focus may not be on reconstructing the original signal, but rather on solving an inference problem in isolation, which classification is an example and offers certain advantage over current methods. Next, the building of a high-resolution compressive Raman spectrometer for gas analysis will be described. A novel cavity-enhanced gas Raman signal generation system was built and developed in a Sagnac spectrometer configuration. Incorporating the idea of compressive sensing into the system further enhances the signal-to-noise ratio and reduces the acquisition time as well as allowing for compactness and portability for use in remote environments. Lastly, improvements and the future potential of this work will be discussed.
Direct Water and Fat Determination in Two-Point Dixon Imaging
(2013-09-16) Rambow, Olen; Clark, John W., Jr.; Ma, Jingfei; Killian, Thomas C.; Kelly, Kevin F.
The Dixon technique is a well-established method in magnetic resonance imaging for obtaining separate images of water and fat. Here we present a generalized solution to the two-point Dixon problem with a geometric interpretation, allowing for flexible echo times and a multi-peak fat model. By simulation and experiment, we have analyzed the dependence on the echo times of the error in the water, fat, and relative background phasor values due to both signal noise and T2* decay. Furthermore, we have demonstrated that broken symmetry due to the multi-peak nature of fat enables direct water and fat determination without phase correction, and we have quantified the reliability of this technique as a function of the echo times. The results may provide valuable guidance for selecting scan parameters to balance the objectives of optimizing fat-water identification, minimizing error in the pixel values, and minimizing total scan time.
Engineering Application-Specific Plasmonic Nanoparticles: Quantitative Measurements and Precise Characterization
(2013-09-16) Anderson, Lindsey; Hafner, Jason H.; Halas, Naomi J.; Kelly, Kevin F.
Nobel metal nanoparticles that exhibit plasmon resonances in the visible and near infrared have been of great interest in recent years. Strong light-matter interactions on the nanoscale have a range of interesting properties that may be useful in applications in medicine, sensing, solar energy harvesting and information processing. Depending on the application, particle materials and geometries can be optimized for performance. A novel method of quantifying individual nanoparticle scattering cross-sections by comparing experiments with analytical theory for gold nanospheres is proposed and utilized. Results show that elongated particles scatter very brightly for their volumes. This brightness is due to a strong longitudinal plasmon resonance that occurs in the near infrared – where gold has minimal loss. Elongated particles, such as nanorods, are therefore, ideal for applications that rely on particles scattering brightly in small spaces, such as biological imaging. Next, gold nanobelts are discussed and characterized. These novel structures are akin to nanowires, but with a small, rectangular cross-sectional geometry. Gold nanobelts are shown to exhibit a strong transverse resonance that has never been reported previously in nanowires. The transverse resonance is shown to shift linearly with crosssectional aspect ratio. Other interesting products from the nanobelt synthesis, tapered and split nanobelts, are discussed. Gold nanobelts also support longitudinal propagating plasmons, and have the smallest cross-sectional area of any elongated plasmonic structure that has been reported to do so. By analyzing the output tip signal of propagating plasmons for nanobelts of different lengths, the decay length is measured. Finite Difference Time Domain simulations and polarization measurements show the fundamental, azimuthally symmetric mode is very strong for thin structures such as these, but decays much more quickly than a higher-order mode, which begins to dominate at longer lengths. The cross-sectional mode area is given, illustrating the high confinement of plasmons in these structures. A figure of merit that takes into account both confinement and propagation length is calculated to be 1300 for the higher-order mode, the highest reported for nanoscale plasmonic waveguides. The high figure of merit makes gold nanobelts excellent candidates for studying strong coupling between plasmonic structures and objects that exhibit quantum behavior.
Evaluating the Effects of Cell Sample Preparation on FTIR Cancer Detection
(2013-09-16) Noelck, Sterling; Drezek, Rebekah A.; Kelly, Kevin F.; Kono, Junichiro
This thesis examines some of the challenges involved with using FTIR spectroscopy for cancer detection including sample preparation and correcting for distortion from cell scattering. Sample preparation affects the spectra differently depending on the cell type, and can lead to significant changes in cancer biomarkers for a given cell type. Biomarkers derived from specific cancer types under one sample preparation are not reliable for other cancer types, and may not be suitable for the same cancer type using a different sample preparation. Cell scattering can also significantly affect the cell spectra, and as a result, correcting for the cell scattering distortion leads to changes in the biomarkers. For reliable cancer detection controlling variability is critical, especially in the complex spectra of biological samples. Standard sample preparation methods and scattering correction post-processing could improve comparison of cancer detection methods.
Experimental and Numerical Investigations of Novel Architectures Applied to Compressive Imaging Systems
(2012-09-05) Turner, Matthew; Kelly, Kevin F.; Baraniuk, Richard G.; Yin, Wotao
A recent breakthrough in information theory known as compressive sensing is one component of an ongoing revolution in data acquisition and processing that guides one to acquire less data yet still recover the same amount of information as traditional techniques, meaning less resources such as time, detector cost, or power are required. Starting from these basic principles, this thesis explores the application of these techniques to imaging. The first laboratory example we introduce is a simple infrared camera. Then we discuss the application of compressive sensing techniques to hyperspectral microscopy, specifically Raman microscopy, which should prove to be a powerful technique to bring the acquisition time for such microscopies down from hours to minutes. Next we explore a novel sensing architecture that uses partial circulant matrices as sensing matrices, which results in a simplified, more robust imaging system. The results of these imaging experiments lead to questions about the performance and fundamental nature of sparse signal recovery with partial circulant compressive sensing matrices. Thus, we present the results of a suite of numerical experiments that show some surprising and suggestive results that could stimulate further theoretical and applied research of partial circulant compressive sensing matrices. We conclude with a look ahead to adaptive sensing procedures that allow real-time, interactive optical signal processing to further reduce the resource demands of an imaging system.
Exploration of Chemical Analysis Techniques for Nanoscale Systems
(2013-09-16) Chang, Albert; Kelly, Kevin F.; Natelson, Douglas; Hafner, Jason H.
As the critical dimensions of many devices, especially electronics, continue to become smaller, the ability to accurately analyze the properties at ever smaller scales becomes necessary. Optical techniques, such as confocal microscopy and various spectroscopies, have produced a wealth of information on larger length scales, above the diffraction limit. Scanning probe techniques, such as scanning tunneling microscopy and atomic force microscopy, provide information with an extremely fine resolution, often on the order of nanometers or angstroms. In this document, plasmon coupling is used to generate large signal increases, with clear future applications toward scanning probe optical spectroscopies. A variation on scanning tunneling microscopy is also used to study the surface structure of environmentally interesting nanoparticles. Traditional Raman spectroscopy is used to examine doped graphene, which is becoming a hot material for future electronic applications.

Browsing by Author "Kelly, Kevin F."

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