PMMA-CNT matrices for vacuum electronic, biosensing and energy applications

Carbon nanotubes (CNTs) are interesting materials with extraordinary properties for various applications. Here, vertically-aligned multiwalled CNTs (VA-MWCNTs) are grown by our dual radio frequency plasma enhanced chemical vapor deposition (PECVD). After optimizing the synthesis processes, these VA-MWCNTs were fabricated in to a series of devices for applications in vacuum electronics, glucose biosensors, glucose biofuel cells, and supercapacitors In particular, we have created the so-called PMMA-CNT matrices (opened-tip CNTs embedded in poly-methyl methacrylate) that are promising components in a novel energy sensing, generation and storage (SGS) system that integrate glucose biosensors, biofuel cells, and supercapacitors. The content of this thesis work is described as follows: 1. We have first optimized the synthesis of VA-MWCNTs by our PECVD technique. The effects of CH4 flow rate and growth duration on the lengths of these CNTs were studied. 2. We have characterized these VA-MWCNTs for electron field emission. We noticed that as grown CNTs suffers from high emission threshold, poor emission density and poor long-term stability. We attempted a series of experiments to understand ways to overcome these problems. First, we decrease the screening effects on VA-MWCNTs by creating arrays of self-assembled CNT bundles that are catalyst-free and opened tips. These bundles are found to enhance the field emission stability and emission density. Subsequently, we have created PMMA-CNT matrices that are excellent electron field emitters with an emission threshold field of more than two-fold lower than that of the as-grown sample. Furthermore, no significant emission degradation was observed after a continuous emission test of 40 hours (versus much shorter tests in reported literatures). Based on the new understanding we learnt from the PMMA-CNT matrices, we further created PMMA-STO-CNT matrices by embedding opened-tip VA-MWCNTs that are coated with strontium titanate (SrTiO3) with PMMA. We found that the PMMA-STO-CNT matrices have all the desired properties of the PMMA-CNT matrices. Furthermore, PMMA-STO-CNT matrices offer much lower emission threshold field, about five-fold lower than that of as grown VA-MWCNTs. The new understandings we obtained are important for practical application of VA-MWCNTs in field emission devices. 3. Subsequently, we have functionalized PMMA-CNT matrices for glucose biosensing. Our biosensor was developed by immobilized glucose oxidase (GOχ) on the opened-tip CNTs exposed on the matrices. The durability, stability and sensitivity of the biosensor were studied. In order to understand the performance of miniaturized glucose biosensors, we have then investigated the effect of working electrode area on the sensitivity and current level of our biosensors. 4. Next, functionalized PMMA-CNT matrices were utilized for energy generation and storage. We found that PMMA-CNT matrices are promising component in glucose/O2 biofuel cells (BFCs) for energy generation. The construction of these BFCs and the effect of the electrode area on the power density of these BFCs were investigated. Then, we have attempted to use PMMA-CNT matrices as supercapacitors for energy storage devices. The performance of these supercapacitors and ways to enhance their performance are discussed. 5. Finally, we further evaluated the concept of energy SGS system that integrated glucose biosensors, biofuel cells, and supercapacitors. This SGS system may be implantable to monitor and control the blood glucose level in our body.

High precision range estimation techniques for multi-path wireless environments

Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic assumptions in practical systems. The performance and complexity of the proposed technique is investigated as well. This study’s results show that selecting bandwidth, center frequency, and SNR levels for each sub-band can adapt positioning accuracy.

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency.

Resource management in location aware cognitive radio networks

Dynamic spectrum access (DSA) aims at utilizing spectral opportunities both in time and frequency domains at any given location, which arise due to variations in spectrum usage. Recently, Cognitive radios (CRs) have been proposed as a means of implementing DSA. In this work we focus on the aspect of resource management in overlaid CRNs. We formulate resource allocation strategies for cognitive radio networks (CRNs) as mathematical optimization problems. Specifically, we focus on two key problems in resource management: Sum Rate Maximization and Maximization of Number of Admitted Users. Since both the above mentioned problems are NP hard due to presence of binary assignment variables, we propose novel graph based algorithms to optimally solve these problems. Further, we analyze the impact of location awareness on network performance of CRNs by considering three cases: Full location Aware, Partial location Aware and Non location Aware. Our results clearly show that location awareness has significant impact on performance of overlaid CRNs and leads to increase in spectrum utilization effciency.