Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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Description
The relationship between biodiversity and ecosystem functioning (BEF) is a central issue in ecology, and a number of recent field experimental studies have greatly improved our understanding of this relationship. Spatial heterogeneity is a ubiquitous characterization of ecosystem processes, and has played a significant role in shaping BEF relationships. The first step towards understanding the effects of spatial heterogeneity on the BEF relationships is to quantify spatial heterogeneity characteristics of key variables of biodiversity and ecosystem functioning, and identify the spatial relationships among these variables. The goal of our research was to address the following research questions based on data collected in 2005 (corresponding to the year when the initial site background information was conducted) and in 2008 (corresponding to the year when removal treatments were conducted) from the Inner Mongolia Grassland Removal Experiment (IMGRE) located in northern China: 1) What are the spatial patterns of soil nutrients, plant biodiversity, and aboveground biomass in a natural grassland community of Inner Mongolia, China? How are they related spatially? and 2) How do removal treatments affect the spatial patterns of soil nutrients, plant biodiversity, and aboveground biomass? Is there any change for their spatial correlations after removal treatments? Our results showed that variables of biodiversity and ecosystem functioning in the natural grassland community would present different spatial patterns, and they would be spatially correlated to each other closely. Removal treatments had a significant effect on spatial structures and spatial correlations of variables, compared to those prior to the removal treatments. The differences in spatial pattern of plant and soil variables and their correlations before and after the biodiversity manipulation may not imply that the results from BEF experiments like IMGRE are invalid. However, they do suggest that the possible effects of spatial heterogeneity on the BEF relationships should be critically evaluated in future studies.
ContributorsYuan, Fei (Author) / Wu, Jianguo (Thesis advisor) / Smith, Andrew T. (Committee member) / Rowe, Helen I (Committee member) / Arizona State University (Publisher)
Created2011
Description
Process variations have become increasingly important for scaled technologies starting at 45nm. The increased variations are primarily due to random dopant fluctuations, line-edge roughness and oxide thickness fluctuation. These variations greatly impact all aspects of circuit performance and pose a grand challenge to future robust IC design. To improve robustness, efficient methodology is required that considers effect of variations in the design flow. Analyzing timing variability of complex circuits with HSPICE simulations is very time consuming. This thesis proposes an analytical model to predict variability in CMOS circuits that is quick and accurate. There are several analytical models to estimate nominal delay performance but very little work has been done to accurately model delay variability. The proposed model is comprehensive and estimates nominal delay and variability as a function of transistor width, load capacitance and transition time. First, models are developed for library gates and the accuracy of the models is verified with HSPICE simulations for 45nm and 32nm technology nodes. The difference between predicted and simulated σ/μ for the library gates is less than 1%. Next, the accuracy of the model for nominal delay is verified for larger circuits including ISCAS'85 benchmark circuits. The model predicted results are within 4% error of HSPICE simulated results and take a small fraction of the time, for 45nm technology. Delay variability is analyzed for various paths and it is observed that non-critical paths can become critical because of Vth variation. Variability on shortest paths show that rate of hold violations increase enormously with increasing Vth variation.
ContributorsGummalla, Samatha (Author) / Chakrabarti, Chaitali (Thesis advisor) / Cao, Yu (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Many products undergo several stages of testing ranging from tests on individual components to end-item tests. Additionally, these products may be further "tested" via customer or field use. The later failure of a delivered product may in some cases be due to circumstances that have no correlation with the product's inherent quality. However, at times, there may be cues in the upstream test data that, if detected, could serve to predict the likelihood of downstream failure or performance degradation induced by product use or environmental stresses. This study explores the use of downstream factory test data or product field reliability data to infer data mining or pattern recognition criteria onto manufacturing process or upstream test data by means of support vector machines (SVM) in order to provide reliability prediction models. In concert with a risk/benefit analysis, these models can be utilized to drive improvement of the product or, at least, via screening to improve the reliability of the product delivered to the customer. Such models can be used to aid in reliability risk assessment based on detectable correlations between the product test performance and the sources of supply, test stands, or other factors related to product manufacture. As an enhancement to the usefulness of the SVM or hyperplane classifier within this context, L-moments and the Western Electric Company (WECO) Rules are used to augment or replace the native process or test data used as inputs to the classifier. As part of this research, a generalizable binary classification methodology was developed that can be used to design and implement predictors of end-item field failure or downstream product performance based on upstream test data that may be composed of single-parameter, time-series, or multivariate real-valued data. Additionally, the methodology provides input parameter weighting factors that have proved useful in failure analysis and root cause investigations as indicators of which of several upstream product parameters have the greater influence on the downstream failure outcomes.
ContributorsMosley, James (Author) / Morrell, Darryl (Committee member) / Cochran, Douglas (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Roberts, Chell (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
Description
A good production schedule in a semiconductor back-end facility is critical for the on time delivery of customer orders. Compared to the front-end process that is dominated by re-entrant product flows, the back-end process is linear and therefore more suitable for scheduling. However, the production scheduling of the back-end process is still very difficult due to the wide product mix, large number of parallel machines, product family related setups, machine-product qualification, and weekly demand consisting of thousands of lots. In this research, a novel mixed-integer-linear-programming (MILP) model is proposed for the batch production scheduling of a semiconductor back-end facility. In the MILP formulation, the manufacturing process is modeled as a flexible flow line with bottleneck stages, unrelated parallel machines, product family related sequence-independent setups, and product-machine qualification considerations. However, this MILP formulation is difficult to solve for real size problem instances. In a semiconductor back-end facility, production scheduling usually needs to be done every day while considering updated demand forecast for a medium term planning horizon. Due to the limitation on the solvable size of the MILP model, a deterministic scheduling system (DSS), consisting of an optimizer and a scheduler, is proposed to provide sub-optimal solutions in a short time for real size problem instances. The optimizer generates a tentative production plan. Then the scheduler sequences each lot on each individual machine according to the tentative production plan and scheduling rules. Customized factory rules and additional resource constraints are included in the DSS, such as preventive maintenance schedule, setup crew availability, and carrier limitations. Small problem instances are randomly generated to compare the performances of the MILP model and the deterministic scheduling system. Then experimental design is applied to understand the behavior of the DSS and identify the best configuration of the DSS under different demand scenarios. Product-machine qualification decisions have long-term and significant impact on production scheduling. A robust product-machine qualification matrix is critical for meeting demand when demand quantity or mix varies. In the second part of this research, a stochastic mixed integer programming model is proposed to balance the tradeoff between current machine qualification costs and future backorder costs with uncertain demand. The L-shaped method and acceleration techniques are proposed to solve the stochastic model. Computational results are provided to compare the performance of different solution methods.
ContributorsFu, Mengying (Author) / Askin, Ronald G. (Thesis advisor) / Zhang, Muhong (Thesis advisor) / Fowler, John W (Committee member) / Pan, Rong (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
Due to the growing concerns on the depletion of petroleum based energy resources and climate change; fuel cell technologies have received much attention in recent years. Proton exchange membrane fuel cell (PEMFCs) features high energy conversion efficiency and nearly zero greenhouse gas emissions, because of its combination of the hydrogen oxidation reaction (HOR) at anode side and oxygen reduction reaction (ORR) at cathode side. Synthesis of Pt nanoparticles supported on multi walled carbon nanotubes (MWCNTs) possess a highly durable electrochemical surface area (ESA) and show good power output on proton exchange membrane (PEM) fuel cell performance. Platinum on multi-walled carbon nanotubes (MWCNTs) support were synthesized by two different processes to transfer PtCl62- from aqueous to organic phase. While the first method of Pt/MWCNTs synthesis involved dodecane thiol (DDT) and octadecane thiol (ODT) as anchoring agent, the second method used ammonium lauryl sulfate (ALS) as the dispersion/anchoring agent. The particle size and distribution of platinum were examined by high-resolution transmission electron microscope (HRTEM). The TEM images showed homogenous distribution and uniform particle size of platinum deposited on the surface of MWCNTs. The single cell fuel cell performance of the Pt/MWCNTs synthesized thiols and ALS based electrode containing 0.2 (anode) and 0.4 mg (cathode) Pt.cm-2 were evaluated using Nafion-212 electrolyte with H2 and O2 gases at 80 oC and ambient pressure. The catalyst synthesis with ALS is relatively simple compared to that with thiols and also showed higher performance (power density reaches about 1070 mW.cm-2). The Electrodes with Pt/MWCNTs nanocatalysts synthesized using ALS were characterized by cyclic voltammetry (CV) for durability evaluation using humidified H2 and N2 gases at room temperature (21 oC) along with commercial Pt/C for comparison. The ESA measured by cyclic voltammetry between 0.15 and 1.2 V showed significant less degradation after 1000 cycles for ALS based Pt/MWCNTs.
ContributorsLiu, Xuan (Author) / Madakannan, Arunachalanadar (Thesis advisor) / Munukutla, Lakshmi (Committee member) / Tamizhmani, Govindasamy (Committee member) / Arizona State University (Publisher)
Created2011
Description
Worldwide, riverine floodplains are among the most endangered landscapes. In response to anthropogenic impacts, riverine restoration projects are considerably increasing. However, there is a paucity of information on how riparian rehabilitation activities impact non-avian wildlife communities. I evaluated herpetofauna abundance, species richness, diversity (i.e., Shannon and Simpson indices), species-specific responses, and riparian microhabitat characteristics along three reaches (i.e., wildland, urban rehabilitated, and urban disturbed) of the Salt River, Arizona. The surrounding uplands of the two urbanized reaches were dominated by the built environment (i.e., Phoenix metropolitan area). I predicted that greater diversity of microhabitat and lower urbanization would promote herpetofauna abundance, richness, and diversity. In 2010, at each reach, I performed herpetofauna visual surveys five times along eight transects (n=24) spanning the riparian zone. I quantified twenty one microhabitat characteristics such as ground substrate, vegetative cover, woody debris, tree stem density, and plant species richness along each transect. Herpetofauna species richness was the greatest along the wildland reach, and the lowest along the urban disturbed reach. The wildland reach had the greatest diversity indices, and diversity indices of the two urban reaches were similar. Abundance of herpetofauna was approximately six times lower along the urban disturbed reach compared to the two other reaches, which had similar abundances. Principal Component Analysis (PCA) reduced microhabitat variables to five factors, and significant differences among reaches were detected. Vegetation structure complexity, vegetation species richness, as well as densities of Prosopis (mesquite), Salix (willow), Populus (cottonwood), and animal burrows had a positive correlation with at least one of the three herpetofauna community parameter quantified (i.e., herpetofauna abundance, species richness, and diversity indices), and had a positive correlation with at least one herpetofauna species. Overall, rehabilitation activities positively influenced herpetofauna abundance and species richness, whereas urbanization negatively influenced herpetofauna diversity indices. Based on herpetofauna/microhabitat correlations established, I developed recommendations regarding microhabitat features that should be created in order to promote herpetofauna when rehabilitating degraded riparian systems. Recommendations are to plant vegetation of different growth habit, provide woody debris, plant Populus, Salix, and Prosopis of various ages and sizes, and to promote small mammal abundance.
ContributorsBanville, Mélanie Josianne (Author) / Bateman, Heather L (Thesis advisor) / Brady, Ward (Committee member) / Stromberg, Juliet (Committee member) / Arizona State University (Publisher)
Created2011
Description
In this work, a new method, "Nanobonding" [1,2] is conceived and researched to bond Si-based surfaces, via nucleation and growth of a 2 D silicon oxide SiOxHx interphase connecting the surfaces at the nanoscale across macroscopic domains. Nanobonding cross-bridges two smooth surfaces put into mechanical contact in an O2/H2O mixed ambient below T <200 °C via arrays of SiOxHx molecules connecting into a continuous macroscopic bonding interphase. Nano-scale surface planarization via wet chemical processing and new spin technology are compared via Tapping Mode Atomic Force Microscopy (TMAFM) , before and after nano-bonding. Nanobonding uses precursor phases, 2D nano-films of beta-cristobalite (beta-c) SiO2, nucleated on Si(100) via the Herbots-Atluri (H-A) method [1]. beta-c SiO2 on Si(100) is ordered and flat with atomic terraces over 20 nm wide, well above 2 nm found in native oxides. When contacted with SiO2 this ultra-smooth nanophase can nucleate and grow domains with cross-bridging molecular strands of hydroxylated SiOx, instead of point contacts. The high density of molecular bonds across extended terraces forms a strong bond between Si-based substrates, nano- bonding [2] the Si and silica. A new model of beta-cristobalite SiO2 with its <110> axis aligned along Si[100] direction is simulated via ab-initio methods in a nano-bonded stack with beta-c SiO2 in contact with amorphous SiO2 (a-SiO2), modelling cross-bridging molecular bonds between beta-c SiO2 on Si(100) and a-SiO2 as during nanobonding. Computed total energies are compared with those found for Si(100) and a-SiO2 and show that the presence of two lattice cells of !-c SiO2 on Si(100) and a-SiO2 lowers energy when compared to Si(100)/ a-SiO2 Shadow cone calculations on three models of beta-c SiO2 on Si(100) are compared with Ion Beam Analysis of H-A processed Si(100). Total surface energy measurements via 3 liquid contact angle analysis of Si(100) after H-A method processing are also compared. By combining nanobonding experiments, TMAFM results, surface energy data, and ab-initio calculations, an atomistic model is derived and nanobonding is optimized. [1] US Patent 6,613,677 (9/2/03), 7,851,365 (12/14/10), [2] Patent Filed: 4/30/09, 10/1/2011
ContributorsWhaley, Shawn D (Author) / Culbertson, Robert J. (Thesis advisor) / Herbots, Nicole (Committee member) / Rez, Peter (Committee member) / Marzke, Robert F (Committee member) / Lindsay, Stuart (Committee member) / Chamberlin, Ralph V (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis describes several experiments based on carbon nanotube nanofludic devices and field-effect transistors. The first experiment detected ion and molecule translocation through one single-walled carbon nanotube (SWCNT) that spans a barrier between two fluid reservoirs. The electrical ionic current is measured. Translocation of small single stranded DNA oligomers is marked by large transient increases in current through the tube and confirmed by a PCR (polymerase chain reaction) analysis. Carbon nanotubes simplify the construction of nanopores, permit new types of electrical measurement, and open new avenues for control of DNA translocation. The second experiment constructed devices in which the interior of a single-walled carbon nanotube field-effect transistor (CNT-FET) acts as a nanofluidic channel that connects two fluid reservoirs, permitting measurement of the electronic properties of the SWCNT as it is wetted by an analyte. Wetting of the inside of the SWCNT by water turns the transistor on, while wetting of the outside has little effect. This finding may provide a new method to investigate water behavior at nanoscale. This also opens a new avenue for building sensors in which the SWCNT functions as an electronic detector. This thesis also presents some experiments that related to nanofabrication, such as construction of FET with tin sulfide (SnS) quantum ribbon. This work demonstrates the application of solution processed IV-VI semiconductor nanostructures in nanoscale devices.
ContributorsCao, Zhai (Author) / Lindsay, Stuart (Thesis advisor) / Vaiana, Sara (Committee member) / Ros, Robert (Committee member) / Marzke, Robert (Committee member) / Shumway, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
Fiber-Wireless (FiWi) network is the future network configuration that uses optical fiber as backbone transmission media and enables wireless network for the end user. Our study focuses on the Dynamic Bandwidth Allocation (DBA) algorithm for EPON upstream transmission. DBA, if designed properly, can dramatically improve the packet transmission delay and overall bandwidth utilization. With new DBA components coming out in research, a comprehensive study of DBA is conducted in this thesis, adding in Double Phase Polling coupled with novel Limited with Share credits Excess distribution method. By conducting a series simulation of DBAs using different components, we found out that grant sizing has the strongest impact on average packet delay and grant scheduling also has a significant impact on the average packet delay; grant scheduling has the strongest impact on the stability limit or maximum achievable channel utilization. Whereas the grant sizing only has a modest impact on the stability limit; the SPD grant scheduling policy in the Double Phase Polling scheduling framework coupled with Limited with Share credits Excess distribution grant sizing produced both the lowest average packet delay and the highest stability limit.
ContributorsZhao, Du (Author) / Reisslein, Martin (Thesis advisor) / McGarry, Michael (Committee member) / Fowler, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
Many nanotechnology-related principles can be demonstrated in a way that is understandable for elementary school-aged children through at-home activity videos. As a part of a National Science Foundation funded grant, Dr. Qing Hua Wang’s research group at Arizona State University developed a nanotechnology-related activity website, Nano@Home, for students. In conjunction with ASU’s virtual Open Door 2021, this creative project aimed to create activity videos based on the Nano@Home website to make the activities more interactive for students.
ContributorsOliver, Ruth Kaylyn (Author) / Wang, Qing Hua (Thesis director) / Krause, Stephen (Committee member) / Materials Science and Engineering Program (Contributor, Contributor) / Watts College of Public Service & Community Solut (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05