Matching Items (255)
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
Intimate coupling of Ti2 photocatalysis and biodegradation (ICPB) offers potential for degrading biorecalcitrant and toxic organic compounds much better than possible with conventional wastewater treatments. This study reports on using a novel sponge-type, Ti2-coated biofilm carrier that shows significant adherence of Ti2 to its exterior and the ability to accumulate biomass in its interior (protected from UV light and free radicals). First, this carrier was tested for ICPB in a continuous-flow photocatalytic circulating-bed biofilm reactor (PCBBR) to mineralize biorecalcitrant organic: 2,4,5-trichlorophenol (TCP). Four mechanisms possibly acting of ICPB were tested separately: TCP adsorption, UV photolysis/photocatalysis, and biodegradation. The carrier exhibited strong TCP adsorption, while photolysis was negligible. Photocatalysis produced TCP-degradation products that could be mineralized and the strong adsorption of TCP to the carrier enhanced biodegradation by relieving toxicity. Validating the ICPB concept, biofilm was protected inside the carriers from UV light and free radicals. ICPB significantly lowered the diversity of the bacterial community, but five genera known to biodegrade chlorinated phenols were markedly enriched. Secondly, decolorization and mineralization of reactive dyes by ICPB were investigated on a refined Ti2-coated biofilm carrier in a PCBBR. Two typical reactive dyes: Reactive Black 5 (RB5) and Reactive Yellow 86 (RY86), showed similar first-order kinetics when being photocatalytically decolorized at low pH (~4-5), which was inhibited at neutral pH in the presence of phosphate or carbonate buffer, presumably due to electrostatic repulsion from negatively charged surface sites on Ti2, radical scavenging by phosphate or carbonate, or both. In the PCBBR, photocatalysis alone with Ti2-coated carriers could remove RB5 and COD by 97% and 47%, respectively. Addition of biofilm inside macroporous carriers maintained a similar RB5 removal efficiency, but COD removal increased to 65%, which is evidence of ICPB despite the low pH. A proposed ICPB pathway for RB5 suggests that a major intermediate, a naphthol derivative, was responsible for most of the residual COD. Finally, three low-temperature sintering methods, called O, D and DN, were compared based on photocatalytic efficiency and Ti2 adherence. The DN method had the best Ti2-coating properties and was a successful carrier for ICPB of RB5 in a PCBBR.
ContributorsLi, Guozheng (Author) / Rittmann, Bruce E. (Thesis advisor) / Halden, Rolf (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2011
Description
Filtration for microfluidic sample-collection devices is desirable for sample selection, concentration, preprocessing, and downstream manipulation, but microfabricating the required sub-micrometer filtration structure is an elaborate process. This thesis presents a simple method to fabricate polydimethylsiloxane (PDMS) devices with an integrated membrane filter that will sample, lyse, and extract the DNA from microorganisms in aqueous environments. An off-the-shelf membrane filter disc was embedded in a PDMS layer and sequentially bound with other PDMS channel layers. No leakage was observed during filtration. This device was validated by concentrating a large amount of cyanobacterium Synechocystis in simulated sample water with consistent performance across devices. After accumulating sufficient biomass on the filter, a sequential electrochemical lysing process was performed by applying 5VDC across the filter. This device was further evaluated by delivering several samples of differing concentrations of cyanobacterium Synechocystis then quantifying the DNA using real-time PCR. Lastly, an environmental sample was run through the device and the amount of photosynthetic microorganisms present in the water was determined. The major breakthroughs in this design are low energy demand, cheap materials, simple design, straightforward fabrication, and robust performance, together enabling wide-utility of similar chip-based devices for field-deployable operations in environmental micro-biotechnology.
ContributorsLecluse, Aurelie (Author) / Meldrum, Deirdre (Thesis advisor) / Chao, Joseph (Thesis advisor) / Westerhoff, Paul (Committee member) / Arizona State University (Publisher)
Created2011
Description
As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).
ContributorsWright, Jillian (Author) / Halden, Rolf (Thesis director) / Driver, Erin (Committee member) / School of Music, Dance and Theatre (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Much of Nepal lacks access to clean drinking water, and many water sources are contaminated with arsenic at concentrations above both World Health Organization and local Nepalese guidelines. While many water treatment technologies exist, it is necessary to identify those that are easily implementable in developing areas. One simple treatment that has gained popularity is biochar—a porous, carbon-based substance produced through pyrolysis of biomass in an oxygen-free environment. Arizona State University’s Engineering Projects in Community Service (EPICS) has partnered with communities in Nepal in an attempt to increase biochar production in the area, as it has several valuable applications including water treatment. Biochar’s arsenic adsorption capability will be investigated in this project with the goal of using the biochar that Nepalese communities produce to remove water contaminants. It has been found in scientific literature that biochar is effective in removing heavy metal contaminants from water with the addition of iron through surface activation. Thus, the specific goal of this research was to compare the arsenic adsorption disparity between raw biochar and iron-impregnated biochar. It was hypothesized that after numerous bed volumes pass through a water treatment column, iron from the source water will accumulate on the surface of raw biochar, mimicking the intentionally iron-impregnated biochar and further increasing contaminant uptake. It is thus an additional goal of this project to compare biochar loaded with iron through an iron-spiked water column and biochar impregnated with iron through surface oxidation. For this investigation, the biochar was crushed and sieved to a size between 90 and 100 micrometers. Two samples were prepared: raw biochar and oxidized biochar. The oxidized biochar was impregnated with iron through surface oxidation with potassium permanganate and iron loading. Then, X-ray fluorescence was used to compare the composition of the oxidized biochar with its raw counterpart, indicating approximately 0.5% iron in the raw and 1% iron in the oxidized biochar. The biochar samples were then added to batches of arsenic-spiked water at iron to arsenic concentration ratios of 20 mg/L:1 mg/L and 50 mg/L:1 mg/L to determine adsorption efficiency. Inductively coupled plasma mass spectrometry (ICP-MS) analysis indicated an 86% removal of arsenic using a 50:1 ratio of iron to arsenic (1.25 g biochar required in 40 mL solution), and 75% removal with a 20:1 ratio (0.5 g biochar required in 40 mL solution). Additional samples were then inserted into a column process apparatus for further adsorption analysis. Again, ICP-MS analysis was performed and the results showed that while both raw and treated biochars were capable of adsorbing arsenic, they were exhausted after less than 70 bed volumes (234 mL), with raw biochar lasting 60 bed volumes (201 mL) and oxidized about 70 bed volumes (234 mL). Further research should be conducted to investigate more affordable and less laboratory-intensive processes to prepare biochar for water treatment.
ContributorsLaird, Ashlyn (Author) / Schoepf, Jared (Thesis director) / Westerhoff, Paul (Committee member) / Chemical Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
An analysis of university flight emissions, carbon neutrality goals, and the global impact of university sanctioned flight.
ContributorsKoehler, Megan Anne (Author) / Halden, Rolf (Thesis director) / Driver, Erin (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Atmospheric particulate matter has a substantial impact on global climate due to its ability to absorb/scatter solar radiation and act as cloud condensation nuclei (CCN). Yet, little is known about marine aerosol, in particular, the carbonaceous fraction. In the present work, particulate matter was collected, using High Volume (HiVol) samplers, onto quartz fiber substrates during a series of research cruises on the Atlantic Ocean. Samples were collected on board the R/V Endeavor on West–East (March–April, 2006) and East–West (June–July, 2006) transects in the North Atlantic, as well as on the R/V Polarstern during a North–South (October–November, 2005) transect along the western coast of Europe and Africa. The aerosol total carbon (TC) concentrations for the West–East (Narragansett, RI, USA to Nice, France) and East–West (Heraklion, Crete, Greece to Narragansett, RI, USA) transects were generally low over the open ocean (0.36±0.14 μg C/m3) and increased as the ship approached coastal areas (2.18±1.37 μg C/m3), due to increased terrestrial/anthropogenic aerosol inputs. The TC for the North–South transect samples decreased in the southern hemisphere with the exception of samples collected near the 15th parallel where calculations indicate the air mass back trajectories originated from the continent. Seasonal variation in organic carbon (OC) was seen in the northern hemisphere open ocean samples with average values of 0.45 μg/m3 and 0.26 μg/m3 for spring and summer, respectively. These low summer time values are consistent with SeaWiFS satellite images that show decreasing chlorophyll a concentration (a proxy for phytoplankton biomass) in the summer. There is also a statistically significant (p<0.05) decline in surface water fluorescence in the summer. Moreover, examination of water–soluble organic carbon (WSOC) shows that the summer aerosol samples appear to have a higher fraction of the lower molecular weight material, indicating that the samples may be more oxidized (aged). The seasonal variation in aerosol content seen during the two 2006 cruises is evidence that a primary biological marine source is a significant contributor to the carbonaceous particulate in the marine atmosphere and is consistent with previous studies of clean marine air masses.
ContributorsHill, Hansina Rae (Author) / Herckes, Pierre (Thesis advisor) / Westerhoff, Paul (Committee member) / Hartnett, Hilairy (Committee member) / Arizona State University (Publisher)
Created2011
Description
Local municipalities in the Phoenix Metropolitan Area have voiced an interest in purchasing alternate source water with lower DBP precursors. Along the primary source is a hydroelectric dam in which water will be diverted from. This project is an assessment of optimizing the potential blends of source water to a water treatment plant in an effort to enable them to more readily meet DBP regulations. To perform this analysis existing water treatment models were used in conjunction with historic water quality sampling data to predict chemical usage necessary to meet DBP regulations. A retrospective analysis was performed for the summer months of 2007 regarding potential for the WTP to reduce cost through optimizing the source water by an average of 30% over the four-month period, accumulating to overall treatment savings of $154 per MG ($82 per AF).
ContributorsRice, Jacelyn (Author) / Westerhoff, Paul (Thesis advisor) / Fox, Peter (Committee member) / Hristovski, Kiril (Committee member) / Arizona State University (Publisher)
Created2011
Description
Early-age cracks in fresh concrete occur mainly due to high rate of surface evaporation and restraint offered by the contracting solid phase. Available test methods that simulate severe drying conditions, however, were not originally designed to focus on evaporation and transport characteristics of the liquid-gas phases in a hydrating cementitious microstructure. Therefore, these tests lack accurate measurement of the drying rate and data interpretation based on the principles of transport properties is limited. A vacuum-based test method capable of simulating early-age cracks in 2-D cement paste is developed which continuously monitors the weight loss and changes to the surface characteristics. 2-D crack evolution is documented using time-lapse photography. Effects of sample size, w/c ratio, initial curing and fiber content are studied. In the subsequent analysis, the cement paste phase is considered as a porous medium and moisture transport is described based on surface mass transfer and internal moisture transport characteristics. Results indicate that drying occurs in two stages: constant drying rate period (stage I), followed by a falling drying rate period (stage II). Vapor diffusion in stage I and unsaturated flow within porous medium in stage II determine the overall rate of evaporation. The mass loss results are analyzed using diffusion-based models. Results show that moisture diffusivity in stage I is higher than its value in stage II by more than one order of magnitude. The drying model is used in conjunction with a shrinkage model to predict the development of capillary pressures. Similar approach is implemented in drying restrained ring specimens to predict 1-D crack width development. An analytical approach relates diffusion, shrinkage, creep, tensile and fracture properties to interpret the experimental data. Evaporation potential is introduced based on the boundary layer concept, mass transfer, and a driving force consisting of the concentration gradient. Effect of wind velocity is reflected on Reynolds number which affects the boundary layer on sample surface. This parameter along with Schmidt and Sherwood numbers are used for prediction of mass transfer coefficient. Concentration gradient is shown to be a strong function of temperature and relative humidity and used to predict the evaporation potential. Results of modeling efforts are compared with a variety of test results reported in the literature. Diffusivity data and results of 1-D and 2-D image analyses indicate significant effects of fibers on controlling early-age cracks. Presented models are capable of predicting evaporation rates and moisture flow through hydrating cement-based materials during early-age drying and shrinkage conditions.
ContributorsBakhshi, Mehdi (Author) / Mobasher, Barzin (Thesis advisor) / Rajan, Subramaniam D. (Committee member) / Zapata, Claudia E. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Sparse learning is a technique in machine learning for feature selection and dimensionality reduction, to find a sparse set of the most relevant features. In any machine learning problem, there is a considerable amount of irrelevant information, and separating relevant information from the irrelevant information has been a topic of focus. In supervised learning like regression, the data consists of many features and only a subset of the features may be responsible for the result. Also, the features might require special structural requirements, which introduces additional complexity for feature selection. The sparse learning package, provides a set of algorithms for learning a sparse set of the most relevant features for both regression and classification problems. Structural dependencies among features which introduce additional requirements are also provided as part of the package. The features may be grouped together, and there may exist hierarchies and over- lapping groups among these, and there may be requirements for selecting the most relevant groups among them. In spite of getting sparse solutions, the solutions are not guaranteed to be robust. For the selection to be robust, there are certain techniques which provide theoretical justification of why certain features are selected. The stability selection, is a method for feature selection which allows the use of existing sparse learning methods to select the stable set of features for a given training sample. This is done by assigning probabilities for the features: by sub-sampling the training data and using a specific sparse learning technique to learn the relevant features, and repeating this a large number of times, and counting the probability as the number of times a feature is selected. Cross-validation which is used to determine the best parameter value over a range of values, further allows to select the best parameter value. This is done by selecting the parameter value which gives the maximum accuracy score. With such a combination of algorithms, with good convergence guarantees, stable feature selection properties and the inclusion of various structural dependencies among features, the sparse learning package will be a powerful tool for machine learning research. Modular structure, C implementation, ATLAS integration for fast linear algebraic subroutines, make it one of the best tool for a large sparse setting. The varied collection of algorithms, support for group sparsity, batch algorithms, are a few of the notable functionality of the SLEP package, and these features can be used in a variety of fields to infer relevant elements. The Alzheimer Disease(AD) is a neurodegenerative disease, which gradually leads to dementia. The SLEP package is used for feature selection for getting the most relevant biomarkers from the available AD dataset, and the results show that, indeed, only a subset of the features are required to gain valuable insights.
ContributorsThulasiram, Ramesh (Author) / Ye, Jieping (Thesis advisor) / Xue, Guoliang (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011