Matching Items (257)
Description
This dissertation provides a fundamental understanding of the impact of bulk polymer properties on the nanometer length scale modulus. The elastic modulus of amorphous organic thin films is examined using a surface wrinkling technique. Potential correlations between thin film behavior and intrinsic properties such as flexibility and chain length are explored. Thermal properties, glass transition temperature (Tg) and the coefficient of thermal expansion, are examined along with the moduli of these thin films. It is found that the nanometer length scale behavior of flexible polymers correlates to its bulk Tg and not the polymers intrinsic size. It is also found that decreases in the modulus of ultrathin flexible films is not correlated with the observed Tg decrease in films of the same thickness. Techniques to circumvent reductions from bulk modulus were also demonstrated. However, as chain flexibility is reduced the modulus becomes thickness independent down to 10 nm. Similarly for this series minor reductions in Tg were obtained. To further understand the impact of the intrinsic size and processing conditions; this wrinkling instability was also utilized to determine the modulus of small organic electronic materials at various deposition conditions. Lastly, this wrinkling instability is exploited for development of poly furfuryl alcohol wrinkles. A two-step wrinkling process is developed via an acid catalyzed polymerization of a drop cast solution of furfuryl alcohol and photo acid generator. The ability to control the surface topology and tune the wrinkle wavelength with processing parameters such as substrate temperature and photo acid generator concentration is also demonstrated. Well-ordered linear, circular, and curvilinear patterns are also obtained by selective ultraviolet exposure and polymerization of the furfuryl alcohol film. As a carbon precursor a thorough understanding of this wrinkling instability can have applications in a wide variety of technologies.
ContributorsTorres, Jessica (Author) / Vogt, Bryan D (Thesis advisor) / Stafford, Christopher M (Committee member) / Richert, Ranko (Committee member) / Rege, Kaushal (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2011
Description
With the increasing focus on developing environmentally benign electronic packages, lead-free solder alloys have received a great deal of attention. Mishandling of packages, during manufacture, assembly, or by the user may cause failure of solder joint. A fundamental understanding of the behavior of lead-free solders under mechanical shock conditions is lacking. Reliable experimental and numerical analysis of lead-free solder joints in the intermediate strain rate regime need to be investigated. This dissertation mainly focuses on exploring the mechanical shock behavior of lead-free tin-rich solder alloys via multiscale modeling and numerical simulations. First, the macroscopic stress/strain behaviors of three bulk lead-free tin-rich solders were tested over a range of strain rates from 0.001/s to 30/s. Finite element analysis was conducted to determine appropriate specimen geometry that could reach a homogeneous stress/strain field and a relatively high strain rate. A novel self-consistent true stress correction method is developed to compensate the inaccuracy caused by the triaxial stress state at the post-necking stage. Then the material property of micron-scale intermetallic was examined by micro-compression test. The accuracy of this measure is systematically validated by finite element analysis, and empirical adjustments are provided. Moreover, the interfacial property of the solder/intermetallic interface is investigated, and a continuum traction-separation law of this interface is developed from an atomistic-based cohesive element method. The macroscopic stress/strain relation and microstructural properties are combined together to form a multiscale material behavior via a stochastic approach for both solder and intermetallic. As a result, solder is modeled by porous plasticity with random voids, and intermetallic is characterized as brittle material with random vulnerable region. Thereafter, the porous plasticity fracture of the solders and the brittle fracture of the intermetallics are coupled together in one finite element model. Finally, this study yields a multiscale model to understand and predict the mechanical shock behavior of lead-free tin-rich solder joints. Different fracture patterns are observed for various strain rates and/or intermetallic thicknesses. The predictions have a good agreement with the theory and experiments.
ContributorsFei, Huiyang (Author) / Jiang, Hanqing (Thesis advisor) / Chawla, Nikhilesh (Thesis advisor) / Tasooji, Amaneh (Committee member) / Mobasher, Barzin (Committee member) / Rajan, Subramaniam D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Current economic conditions necessitate the extension of service lives for a variety of aerospace systems. As a result, there is an increased need for structural health management (SHM) systems to increase safety, extend life, reduce maintenance costs, and minimize downtime, lowering life cycle costs for these aging systems. The implementation of such a system requires a collaborative research effort in a variety of areas such as novel sensing techniques, robust algorithms for damage interrogation, high fidelity probabilistic progressive damage models, and hybrid residual life estimation models. This dissertation focuses on the sensing and damage estimation aspects of this multidisciplinary topic for application in metallic and composite material systems. The primary means of interrogating a structure in this work is through the use of Lamb wave propagation which works well for the thin structures used in aerospace applications. Piezoelectric transducers (PZTs) were selected for this application since they can be used as both sensors and actuators of guided waves. Placement of these transducers is an important issue in wave based approaches as Lamb waves are sensitive to changes in material properties, geometry, and boundary conditions which may obscure the presence of damage if they are not taken into account during sensor placement. The placement scheme proposed in this dissertation arranges piezoelectric transducers in a pitch-catch mode so the entire structure can be covered using a minimum number of sensors. The stress distribution of the structure is also considered so PZTs are placed in regions where they do not fail before the host structure. In order to process the data from these transducers, advanced signal processing techniques are employed to detect the presence of damage in complex structures. To provide a better estimate of the damage for accurate life estimation, machine learning techniques are used to classify the type of damage in the structure. A data structure analysis approach is used to reduce the amount of data collected and increase computational efficiency. In the case of low velocity impact damage, fiber Bragg grating (FBG) sensors were used with a nonlinear regression tool to reconstruct the loading at the impact site.
ContributorsCoelho, Clyde (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Wu, Tong (Committee member) / Das, Santanu (Committee member) / Rajadas, John (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2011
Description
Ordered mesoporous materials have tunable pore sizes between 2 and 50 nm and are characterized by ordered pore structures and high surface areas (~1000 m2/g). This makes them particularly favorable for a number of membrane applications such as protein separation, polymer extrusion, nanowire fabrication and membrane reactors. These membranes can be fabricated as top-layers on macroporous supports or as embedded membranes in a dense matrix. The first part of the work deals with the hydrothermal synthesis and water-vapor/oxygen separation properties of supported MCM-48 and a new Al-MCM-48 type membrane for potential use in air conditioning systems. Knudsen-type permeation is observed in these membranes. The combined effect of capillary condensation and the aluminosilicate matrix resulted in the highest separation factor (142) in Al-MCM-48 membranes, with a water vapor permeance of 6×10-8mol/m2Pas. The second part focuses on synthesis of embedded mesoporous silica membranes with helically ordered pores by a novel Counter Diffusion Self-Assembly (CDSA) method. This method is an extension of the interfacial synthesis method for fiber synthesis using tetrabutylorthosilicate (TBOS) and cetyltrimethylammonium bromide (CTAB) as the silica source and surfactant respectively. The initial part of this study determined the effect of TBOS height and humidity on fiber formation. From this study, the range of TBOS heights for best microscopic and macroscopic ordering were established. Next, the CDSA method was used to successfully synthesize membranes, which were characterized to have good support plugging and an ordered pore structure. Factors that influence membrane synthesis and plug microstructure were determined. SEM studies revealed the presence of gaps between the plugs and support pores, which occur due to shrinking of the plug on drying. Development of a novel liquid deposition method to seal these defects constituted the last part of this work. Post sealing, excess silica was removed by etching with hydrofluoric acid. Membrane quality was evaluated at each step using SEM and gas permeation measurements. After surfactant removal by liquid extraction, the membranes exhibited an O2 permeance of 1.65x10-6mol/m2.Pa.s and He/O2 selectivity of 3.30. The successful synthesis of this membrane is an exciting new development in the area of ordered mesoporous membrane technology.
ContributorsSeshadri, Shriya (Author) / Lin, Jerry Y. S. (Thesis advisor) / Dai, Lenore (Committee member) / Rege, Kaushal (Committee member) / Smith, David J. (Committee member) / Vogt, Bryan (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
Temporary bonding-debonding of flexible plastic substrates to rigid carriers may facilitate effective substrate handling by automated tools for manufacture of flexible microelectronics. The primary challenges in implementing practical temporary bond-debond technology originate from the stress that is developed during high temperature processing predominately through thermal-mechanical property mismatches between carrier, adhesive and substrate. These stresses are relaxed through bowing of the bonded system (substrate-adhesive-carrier), which causes wafer handling problems, or through delamination of substrate from rigid carrier. Another challenge inherent to flexible plastic substrates and linked to stress is their dimensional instability, which may manifest itself in irreversible deformation upon heating and cooling cycles. Dimensional stability is critical to ensure precise registration of different layers during photolithography. The global objective of this work is to determine comprehensive experimental characterization and develop underlying fundamental engineering concept that could enable widespread adoption and scale-up of temporary bonding processing protocols for flexible microelectronics manufacturing. A series of carriers with different coefficient of thermal expansion (CTE), modulus and thickness were investigated to correlate the thermo-mechanical properties of carrier with deformation behavior of bonded systems. The observed magnitude of system bow scaled with properties of carriers according to well-established Stoney's equation. In addition, rheology of adhesive impacted the deformation of bonded system. In particular, distortion-bowing behavior correlated directly with the relative loss factor of adhesive and flexible plastic substrate. Higher loss factor of adhesive compared to that of substrate allowed the stress to be relaxed with less bow, but led to significantly greater dimensional distortion. Conversely, lower loss factor of adhesive allowed less distortion but led to larger wafer bow. A finite element model using ANSYS was developed to predict the trend in bow-distortion of bonded systems as a function of the viscoelastic properties of adhesive. Inclusion of the viscoelasticity of flexible plastic substrate itself was critical to achieving good agreement between simulation and experiment. Simulation results showed that there is a limited range within which tuning the rheology of adhesive can control the stress-distortion. Therefore, this model can aid in design of new adhesive formulations compatible with different processing requirements of various flexible microelectronics applications.
ContributorsHaq, Jesmin (Author) / Raupp, Gregory B (Thesis advisor) / Vogt, Bryan D (Thesis advisor) / Dai, Lenore (Committee member) / Loy, Douglas (Committee member) / Li, Jian (Committee member) / Arizona State University (Publisher)
Created2011
Description
Mesoporous materials that possess large surface area, tunable pore size, and ordered structures are attractive features for many applications such as adsorption, protein separation, enzyme encapsulation and drug delivery as these materials can be tailored to host different guest molecules. Films provide a model system to understand how the pore orientation impacts the potential for loading and release of selectively sized molecules. This research work aims to develop structure-property relationships to understand how pore size, geometry, and surface hydrophobicity influence the loading and release of drug molecules. In this study, the pore size is systematically varied by incorporating pore-swelling agent of polystyrene oligomers (hPS) to soft templated mesoporous carbon films fabricated by cooperative assembly of poly(styrene-block-ethylene oxide) (SEO) with phenolic resin. To examine the impact of morphology, different compositions of amphiphilic triblock copolymer templates, poly(ethylene oxide)-block-poly(propylene oxide)-block-poly(ethylene oxide) (PEO-PPO-PEO), are used to form two-dimensional hexagonal and cubic mesostructures. Lastly, the carbonization temperature provides a handle to tune the hydrophobicity of the film. These mesoporous films are then utilized to understand the uptake and release of a model drug Mitoxantrone dihydrochloride from nanostructured materials. The largest pore size (6nm) mesoporous carbon based on SEO exhibits the largest uptake (3.5μg/cm2); this is attributed to presence of larger internal volume compared to the other two films. In terms of release, a controlled response is observed for all films with the highest release for the 2nm cubic film (1.45 μg/cm2) after 15 days, but this is only 56 % of the drug loaded. Additionally, the surface hydrophobicity impacts the fraction of drug release with a decrease from 78% to 43%, as the films become more hydrophobic when carbonized at higher temperatures. This work provides a model system to understand how pore morphology, size and chemistry influence the drug loading and release for potential implant applications.
ContributorsLabiano, Alpha (Author) / Vogt, Bryan (Thesis advisor) / Rege, Kaushal (Committee member) / Dai, Lenore (Committee member) / Potta, Thrimoorthy (Committee member) / Arizona State University (Publisher)
Created2011
Description
Biological membranes are critical to cell sustainability by selectively permeating polar molecules into the intracellular space and providing protection to the interior organelles. Biomimetic membranes (model cell membranes) are often used to fundamentally study the lipid bilayer backbone structure of the biological membrane. Lipid bilayer membranes are often supported using inorganic materials in an effort to improve membrane stability and for application to novel biosensing platforms. Published literature has shown that a variety of dense inorganic materials with various surface properties have been investigated for the study of biomimetic membranes. However, literature does not adequately address the effect of porous materials or supports with varying macroscopic geometries on lipid bilayer membrane behavior. The objective of this dissertation is to present a fundamental study on the synthesis of lipid bilayer membranes supported by novel inorganic supports in an effort to expand the number of available supports for biosensing technology. There are two fundamental areas covered including: (1) synthesis of lipid bilayer membranes on porous inorganic materials and (2) synthesis and characterization of cylindrically supported lipid bilayer membranes. The lipid bilayer membrane formation behavior on various porous supports was studied via direct mass adsorption using a quartz crystal microbalance. Experimental results demonstrate significantly different membrane formation behaviors on the porous inorganic supports. A lipid bilayer membrane structure was formed only on SiO2 based surfaces (dense SiO2 and silicalite, basic conditions) and gamma-alumina (acidic conditions). Vesicle monolayer adsorption was observed on gamma-alumina (basic conditions), and yttria stabilized zirconia (YSZ) of varying roughness. Parameters such as buffer pH, surface chemistry and surface roughness were found to have a significant impact on the vesicle adsorption kinetics. Experimental and modeling work was conducted to study formation and characterization of cylindrically supported lipid bilayer membranes. A novel sensing technique (long-period fiber grating refractometry) was utilized to measure the formation mechanism of lipid bilayer membranes on an optical fiber. It was found that the membrane formation kinetics on the fiber was similar to its planar SiO2 counterpart. Fluorescence measurements verified membrane transport behavior and found that characterization artifacts affected the measured transport behavior.
ContributorsEggen, Carrie (Author) / Lin, Jerry Y.S. (Thesis advisor) / Dai, Lenore (Committee member) / Rege, Kaushal (Committee member) / Thornton, Trevor (Committee member) / Vogt, Bryan (Committee member) / Arizona State University (Publisher)
Created2011
Description
This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree models. Associative classifiers can achieve high accuracy, but the combination of many rules is difficult to interpret. Rule condition subset selection (RCSS) methods for associative classification are considered. RCSS aims to prune the rule conditions into a subset via feature selection. The subset then can be summarized into rule-based classifiers. Experiments show that classifiers after RCSS can substantially improve the classification interpretability without loss of accuracy. An ensemble feature selection method is proposed to learn Markov blankets for either discrete or continuous networks (without linear, Gaussian assumptions). The method is compared to a Bayesian local structure learning algorithm and to alternative feature selection methods in the causal structure learning problem. Feature selection is also used to enhance the interpretability of time series classification. Existing time series classification algorithms (such as nearest-neighbor with dynamic time warping measures) are accurate but difficult to interpret. This research leverages the time-ordering of the data to extract features, and generates an effective and efficient classifier referred to as a time series forest (TSF). The computational complexity of TSF is only linear in the length of time series, and interpretable features can be extracted. These features can be further reduced, and summarized for even better interpretability. Lastly, two variable importance measures are proposed to reduce the feature selection bias in tree-based ensemble models. It is well known that bias can occur when predictor attributes have different numbers of values. Two methods are proposed to solve the bias problem. One uses an out-of-bag sampling method called OOBForest, and the other, based on the new concept of a partial permutation test, is called a pForest. Experimental results show the existing methods are not always reliable for multi-valued predictors, while the proposed methods have advantages.
ContributorsDeng, Houtao (Author) / Runger, George C. (Thesis advisor) / Lohr, Sharon L (Committee member) / Pan, Rong (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2011
Description
Hydropower generation is one of the clean renewable energies which has received great attention in the power industry. Hydropower has been the leading source of renewable energy. It provides more than 86% of all electricity generated by renewable sources worldwide. Generally, the life span of a hydropower plant is considered as 30 to 50 years. Power plants over 30 years old usually conduct a feasibility study of rehabilitation on their entire facilities including infrastructure. By age 35, the forced outage rate increases by 10 percentage points compared to the previous year. Much longer outages occur in power plants older than 20 years. Consequently, the forced outage rate increases exponentially due to these longer outages. Although these long forced outages are not frequent, their impact is immense. If reasonable timing of rehabilitation is missed, an abrupt long-term outage could occur and additional unnecessary repairs and inefficiencies would follow. On the contrary, too early replacement might cause the waste of revenue. The hydropower plants of Korea Water Resources Corporation (hereafter K-water) are utilized for this study. Twenty-four K-water generators comprise the population for quantifying the reliability of each equipment. A facility in a hydropower plant is a repairable system because most failures can be fixed without replacing the entire facility. The fault data of each power plant are collected, within which only forced outage faults are considered as raw data for reliability analyses. The mean cumulative repair functions (MCF) of each facility are determined with the failure data tables, using Nelson's graph method. The power law model, a popular model for a repairable system, can also be obtained to represent representative equipment and system availability. The criterion-based analysis of HydroAmp is used to provide more accurate reliability of each power plant. Two case studies are presented to enhance the understanding of the availability of each power plant and represent economic evaluations for modernization. Also, equipment in a hydropower plant is categorized into two groups based on their reliability for determining modernization timing and their suitable replacement periods are obtained using simulation.
ContributorsKwon, Ogeuk (Author) / Holbert, Keith E. (Thesis advisor) / Heydt, Gerald T (Committee member) / Pan, Rong (Committee member) / Arizona State University (Publisher)
Created2011