Melvin A. Herlin and Sanborn C. Brown. / "May 3, 1948." / Army Signal Corps Contract No. W-36-039 sc-32037.

Laser Induced Breakdown Spectroscopy LIBS is a fast non-contact technique for the analysis of the elemental composition using spectral information of the emission from a laser-induced plasma. For the LIBS studies in this thesis the focus has been in using very low energy, microjoule pulses in order to give high spatial resolution and minimize the laser system requirements. This is a regime that we refer to as microLIBS. Under such conditions it is important to maximize the signal detected to give the lowest limit of detection LOD possible. One technique to improve the signal to noise ratios is by coupling LIBS with Laser Induced Fluorescence. This is a technique where the _rst pulse creates a vapor plume and the second pulse tuned to a resonant absorption line of the species of interest re-excites the plume. We term this technique as Laser ablation Laser Induced Fluorescence LA-LIF. We have been investigating the performance of LA-LIF at low pulse energies (_ 1 mJ for both pulses) for the detection of elemental contaminants in water. This technique allows reasonable performance compared to high energy singlepulse LIBS, but at a much reduced total energy expenditure. This allows LODs in the parts per billion range ppb range which typically cannot be obtained with low energy single pulse probing of the systems. This approach or exceeds the sensitivities which can be obtained with many shots using much larger energy systems. In this thesis we investigated the performance of LIBS at low pulse energies for the detection of Pb as a contaminant in water. An LOD of 70 ppb was obtained for an accumulation of 100 shots with the ablation laser pulse energy of 250 _J and an excitation laser pulse energy of 8 _J. A systematic study of the detector conditions was made for the system for the detection of Pb. Scaling laws for the LOD in terms of the pump and probe energies were measured and also the e_ect of detector gain, the gate delay and the gate width were studied. In this thesis LIBS and LA-LIF were also used to analyze ultralow volumes of analyte in liquids in microuidic geometries. LIBS was applied for the detection of Na in liquid droplets in a microuidic system. The detection of Na as low as 360 femtograms was demonstrated for 100 shots integrated in this system. An LOD of 7 ppm for Pb for 100 shot accumulation was demonstrated using the LA-LIF technique on an 18 _m diameter microdroplet. To study the laser interaction with the water targets the MEDUSA one dimensional hydrocode was used. The propagation of the shockwave and plume dynamics were studied using this modeling code. The expansion of the plume was studied and compared to experimentally measured values and to physical models for blast wave expansion and stagnation. Two preconcentration techniques were also studied, one of which used a wood-chip as a substrate to absorb the analyte liquid and wick the salt on to the surface for analysis and the other used an electroplating technique to plate the analyte metal as a thin _lm on a substrate metal used as a cathode. The electroplating method for preconcentration was also studied using a microchip laser and a LOD of 6.4 ppb for Pb in water was obtained for an accumalation of 200,000 shots. / Photonics and Plasmas

Volunteer canola (<i>Brassica napus</i> L.) has become an abundant weed in western Canadian cropping systems. Modern canola cultivars are strong competitors and produce large seed yields, however seed shattering during harvest creates large volunteer seedbanks. The segregation of hybrid trait and changes in variability of traits may allow successive generations of volunteer <i>B. napus</i> weeds to display different levels of fitness and other traits. Three cultivars: 2 hybrid, and 1 open-pollinated at three consecutive generations: G1, the initial crop; G2, first generation of volunteers; and G3 the second generation of volunteers, were used to evaluate the competitive ability, fitness and population dynamics of volunteer canola when grown as a weed in wheat (<i>Triticum aestivum</i> L.). Traits including seed, biomass, and pod production, plant height, seed weight, dormancy, and competitive ability were measured. In all traits but height and seed weight, hybrid breakdown occurred, as the hybrid G1displayed greater mean values than the G2 generation. Hybrids commonly showed the highest mean values of various traits in the G1, lowest mean values in the G2. Hybrid G3 populations produced mean values not different from the G1 or G2 generations for many traits. The open-pollinated cultivar displayed mean values for all traits which did not vary across generations. Generational differences in <i>B. napus</i> seedlings resulted in differences in wheat yield losses. <i>B. napus</i> densities at maturity provided a more robust model of wheat yield loss, as there were differences in wheat yield losses due to the interaction of generation and cultivar of <i>B. napus</i>. Commercial seed generations were the most competitive and fit plants, while volunteer generations were less competitive, and not as fit.

In the last three decades, the electronic industry has registered a tremendous progress. The continuous and aggressive downsizing of the transistor feature sizes (CMOS scaling) has been the main driver of the astonishing growth and advancement of microelectronic industry. Currently, the CMOS scaling is almost reaching its limits. The gate oxide is now only a few atomic layers thick, and this extremely thin oxide causes a huge leakage current through the oxide. Therefore, a further reduction of the gate oxide thickness is extremely difficult and new materials with higher dielectric constant are being explored. However, the phenomena of oxide breakdown and reliability are still serious issues in these thin oxides. Oxide breakdown exhibits a soft breakdown behavior at low voltages, and this is posing as one of the most crucial reliability issues for scaling of the ultra-thin oxides. In addition, the stress-induced leakage current (SILC) due to oxide has emerged as a scaling problem for the non-volatile memory technologies. In this dissertation, a percolation modeling approach is introduced to study and understand the dramatic changes in the conductivity of a disordered medium. Two different simulation methods of percolative conduction, the site and bond percolation, are studied here. These are used in simulating the post-breakdown conduction inside the oxide. Adopting a Monte-Carlo method, oxide breakdown is modeled using a 2-D percolation theory. The breakdown statistics and post-breakdown characteristics of the oxide are computed using this model. In this work, the effects of different physical parameters, such as dimension and the applied stress are studied. The simulation results show that a thinning of oxide layer and increasing the oxide area result in softening of breakdown. It is observed that the breakdown statistics appear to follow Weibull characteristics. As revealed by simulations, the Weibull slope changes linearly with oxide thickness, while not having a significant change when the area is varied and when the amount of the applied stress is varied. It is shown that the simulation results are well correlated with the experimental data reported in the literature. In this thesis, studying the conduction through the oxide using percolation model, it was discovered that a critical or a quasi-critical phenomenon occurs depending on the oxide dimensions. The criticality of the phase-transition results in a hard breakdown while the soft breakdown occurs due to a quasi-critical nature of percolation for ultra-thin oxides. In the later part of the thesis, a quantum percolation model is studied in order to explain and model the stress induced leakage current. It is explained that due to the wave nature of electrons, the SILC can be modeled as a tunneling path through the stressed oxide with the smaller tunneling threshold compared to the virgin oxide. In addition to the percolation model, a Markov chain theory is introduced to simulate the movement of electron as a random walk inside the oxide, and the breakdown is simulated using this random-walk of electron through the accumulated traps inside the oxide. It is shown that the trapping-detrapping of electrons results in an electrical noise in the post-breakdown current having 1/f noise characteristics. Using simulation of a resistor network with Markov theory, the conductance of the oxide is computed. An analytical study of a 2-D site percolation system is conducted using recursive methods and useful closed-form expressions are derived for specialized networks.

In the last three decades, the electronic industry has registered a tremendous progress. The continuous and aggressive downsizing of the transistor feature sizes (CMOS scaling) has been the main driver of the astonishing growth and advancement of microelectronic industry. Currently, the CMOS scaling is almost reaching its limits. The gate oxide is now only a few atomic layers thick, and this extremely thin oxide causes a huge leakage current through the oxide. Therefore, a further reduction of the gate oxide thickness is extremely difficult and new materials with higher dielectric constant are being explored. However, the phenomena of oxide breakdown and reliability are still serious issues in these thin oxides. Oxide breakdown exhibits a soft breakdown behavior at low voltages, and this is posing as one of the most crucial reliability issues for scaling of the ultra-thin oxides. In addition, the stress-induced leakage current (SILC) due to oxide has emerged as a scaling problem for the non-volatile memory technologies. In this dissertation, a percolation modeling approach is introduced to study and understand the dramatic changes in the conductivity of a disordered medium. Two different simulation methods of percolative conduction, the site and bond percolation, are studied here. These are used in simulating the post-breakdown conduction inside the oxide. Adopting a Monte-Carlo method, oxide breakdown is modeled using a 2-D percolation theory. The breakdown statistics and post-breakdown characteristics of the oxide are computed using this model. In this work, the effects of different physical parameters, such as dimension and the applied stress are studied. The simulation results show that a thinning of oxide layer and increasing the oxide area result in softening of breakdown. It is observed that the breakdown statistics appear to follow Weibull characteristics. As revealed by simulations, the Weibull slope changes linearly with oxide thickness, while not having a significant change when the area is varied and when the amount of the applied stress is varied. It is shown that the simulation results are well correlated with the experimental data reported in the literature. In this thesis, studying the conduction through the oxide using percolation model, it was discovered that a critical or a quasi-critical phenomenon occurs depending on the oxide dimensions. The criticality of the phase-transition results in a hard breakdown while the soft breakdown occurs due to a quasi-critical nature of percolation for ultra-thin oxides. In the later part of the thesis, a quantum percolation model is studied in order to explain and model the stress induced leakage current. It is explained that due to the wave nature of electrons, the SILC can be modeled as a tunneling path through the stressed oxide with the smaller tunneling threshold compared to the virgin oxide. In addition to the percolation model, a Markov chain theory is introduced to simulate the movement of electron as a random walk inside the oxide, and the breakdown is simulated using this random-walk of electron through the accumulated traps inside the oxide. It is shown that the trapping-detrapping of electrons results in an electrical noise in the post-breakdown current having 1/f noise characteristics. Using simulation of a resistor network with Markov theory, the conductance of the oxide is computed. An analytical study of a 2-D site percolation system is conducted using recursive methods and useful closed-form expressions are derived for specialized networks.

Volunteer canola (<i>Brassica napus</i> L.) has become an abundant weed in western Canadian cropping systems. Modern canola cultivars are strong competitors and produce large seed yields, however seed shattering during harvest creates large volunteer seedbanks. The segregation of hybrid trait and changes in variability of traits may allow successive generations of volunteer <i>B. napus</i> weeds to display different levels of fitness and other traits. Three cultivars: 2 hybrid, and 1 open-pollinated at three consecutive generations: G1, the initial crop; G2, first generation of volunteers; and G3 the second generation of volunteers, were used to evaluate the competitive ability, fitness and population dynamics of volunteer canola when grown as a weed in wheat (<i>Triticum aestivum</i> L.). Traits including seed, biomass, and pod production, plant height, seed weight, dormancy, and competitive ability were measured. In all traits but height and seed weight, hybrid breakdown occurred, as the hybrid G1displayed greater mean values than the G2 generation. Hybrids commonly showed the highest mean values of various traits in the G1, lowest mean values in the G2. Hybrid G3 populations produced mean values not different from the G1 or G2 generations for many traits. The open-pollinated cultivar displayed mean values for all traits which did not vary across generations. Generational differences in <i>B. napus</i> seedlings resulted in differences in wheat yield losses. <i>B. napus</i> densities at maturity provided a more robust model of wheat yield loss, as there were differences in wheat yield losses due to the interaction of generation and cultivar of <i>B. napus</i>. Commercial seed generations were the most competitive and fit plants, while volunteer generations were less competitive, and not as fit.

This thesis presents a comprehensive assessment of breakdown and operational voltage constraints in state-of-the-art silicon-germanium (SiGe) heterojunction bipolar transistor (HBT) BiCMOS technology. Technology scaling of SiGe HBTs for high frequency performance results on lower breakdown voltages, making operating voltage constraints an increasingly vital reliability consideration in SiGe HBTs from both a device and circuits perspective.

Conventionally, metal halide lamps were struck by voltages higher than those required for breaking down the electrodes to ensure successful ignition. These high ignition voltages may hurt the electrodes to some extent, leading to a shorter lamp lifecycle. In practice, the breakdown voltage can be affected by the dark current which occurs when a voltage is applied on lamp before the electrodes have been broken down. A lamp model to account for the dark current is derived from the test results. Three ignition schemes with single-pulse, multiple pulses and step voltage are used for describing the effect of the dark current on the breakdown voltage. Experimental results exhibit that the breakdown voltage can be lowered by applying a higher dark current or allotting more times of dark current to the lamp. The investigation provides useful information for the design of the ignition circuit.

Smart devices with multiple on-board sensors, networked through wired or wireless links, are distributed in physical systems and environments. Broad applications of such sensor networks include manufacturing quality control and wireless sensor systems. In the operation of sensor systems, robust methods for retrieving reliable information from sensor systems are crucial in the presence of potential sensor failures. Existence of sensor redundancy is one of the main drivers for the robustness or fault tolerance capability of a sensor system. The redundancy degree of sensors plays two important roles pertaining to the robustness of a sensor network. First, the redundancy degree provides proper parameter values for robust estimator; second, we can calculate the fault tolerance capability of a sensor network from the redundancy degree. Given this importance of the redundancy degree, this dissertation presents efficient algorithms based on matroid theory to compute the redundancy degree of a clustered sensor network. In the efficient algorithms, a cluster pattern of a sensor network allows us to decompose a large sensor network into smaller sub-systems, from which the redundancy degree can be found more efficiently. Finally, the robustness analysis as well as its algorithm procedure is illustrated using examples of a multi-station assembly process and calibration of wireless sensor networks.

As technologies continue advancing, semiconductor devices with dimensions in nanometers have entered all spheres of human life. This research deals with both the statistical aspect of reliability and some electrical aspect of reliability characterization. As an example of nano devices, TaO_x-based high k dielectric thin &#64257;lms are studied on the failure mode identi&#64257;cation, accelerated life testing, lifetime projection, and failure rate estimation. Experiment and analysis on dielectric relaxation and transient current show that the relaxation current of high k dielectrics is distinctive to the trapping/detrapping current of SiO₂; high k &#64257;lms have a lower leakage current but a higher relaxation current than SiO₂. Based on the connection between polarization-relaxation and &#64257;lm integrity demonstrated in ramped voltage stress tests, a new method of breakdown detection is proposed. It monitors relaxation during the test, and uses the disappearing of relaxation current as the signal of a breakdown event. This research develops a Bayesian approach which is suitable to reliability estimation and prediction of current and future generations of nano devices. It combines the Weibull lifetime distribution with the empirical acceleration relationship, and put the model parameters into a hierarchical Bayesian structure. The value of the Bayesian approach lies in that it can fully utilize available information in modeling uncertainty and provide cogent prediction with limited resources in a reasonable period of time. Markov chain Monte Carlo simulation is used for posterior inference of the reliability projection and for sensitivity analysis over a variety of vague priors. Time-to-breakdown data collected in the accelerated life tests also are modeled with a bathtub failure rate curve. The decreasing failure rate is estimated with a non-parametric Bayesian approach, and the constant failure rate is estimated with a regular parametric Bayesian approach. This method can provide a fast and reliable estimation of failure rate for burn-in optimization when only a small sample of data is available.