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- Genre: Doctoral Dissertation
Description
The semiconductor field of Photovoltaics (PV) has experienced tremendous growth, requiring curricula to consider ways to promote student success. One major barrier to success students may face when learning PV is the development of misconceptions. The purpose of this work was to determine the presence and prevalence of misconceptions students may have for three PV semiconductor phenomena; Diffusion, Drift and Excitation. These phenomena are emergent, a class of phenomena that have certain characteristics. In emergent phenomena, the individual entities in the phenomena interact and aggregate to form a self-organizing pattern that can be observed at a higher level. Learners develop a different type of misconception for these phenomena, an emergent misconception. Participants (N=41) completed a written protocol. The pilot study utilized half of these protocols (n = 20) to determine the presence of both general and emergent misconceptions for the three phenomena. Once the presence of both general and emergent misconceptions was confirmed, all protocols (N=41) were analyzed to determine the presence and prevalence of general and emergent misconceptions, and to note any relationships among these misconceptions (full study). Through written protocol analysis of participants' responses, numerous codes emerged from the data for both general and emergent misconceptions. General and emergent misconceptions were found in 80% and 55% of participants' responses, respectively. General misconceptions indicated limited understandings of chemical bonding, electricity and magnetism, energy, and the nature of science. Participants also described the phenomena using teleological, predictable, and causal traits, indicating participants had misconceptions regarding the emergent aspects of the phenomena. For both general and emergent misconceptions, relationships were observed between similar misconceptions within and across the three phenomena, and differences in misconceptions were observed across the phenomena. Overall, the presence and prevalence of both general and emergent misconceptions indicates that learners have limited understandings of the physical and emergent mechanisms for the phenomena. Even though additional work is required, the identification of specific misconceptions can be utilized to enhance semiconductor and PV course content. Specifically, changes can be made to curriculum in order to limit the formation of misconceptions as well as promote conceptual change.
ContributorsNelson, Katherine G (Author) / Brem, Sarah K. (Thesis advisor) / Mckenna, Ann F (Thesis advisor) / Hilpert, Jonathan (Committee member) / Honsberg, Christiana (Committee member) / Husman, Jenefer (Committee member) / Arizona State University (Publisher)
Created2014
Description
Increasing computational demands in data centers require facilities to operate at higher ambient temperatures and at higher power densities. Conventionally, data centers are cooled with electrically-driven vapor-compressor equipment. This paper proposes an alternative data center cooling architecture that is heat-driven. The source is heat produced by the computer equipment. This dissertation details experiments investigating the quantity and quality of heat that can be captured from a liquid-cooled microprocessor on a computer server blade from a data center. The experiments involve four liquid-cooling setups and associated heat-extraction, including a radical approach using mineral oil. The trials examine the feasibility of using the thermal energy from a CPU to drive a cooling process. Uniquely, the investigation establishes an interesting and useful relationship simultaneously among CPU temperatures, power, and utilization levels. In response to the system data, this project explores the heat, temperature and power effects of adding insulation, varying water flow, CPU loading, and varying the cold plate-to-CPU clamping pressure. The idea is to provide an optimal and steady range of temperatures necessary for a chiller to operate. Results indicate an increasing relationship among CPU temperature, power and utilization. Since the dissipated heat can be captured and removed from the system for reuse elsewhere, the need for electricity-consuming computer fans is eliminated. Thermocouple readings of CPU temperatures as high as 93°C and a calculated CPU thermal energy up to 67Wth show a sufficiently high temperature and thermal energy to serve as the input temperature and heat medium input to an absorption chiller. This dissertation performs a detailed analysis of the exergy of a processor and determines the maximum amount of energy utilizable for work. Exergy as a source of realizable work is separated into its two contributing constituents: thermal exergy and informational exergy. The informational exergy is that usable form of work contained within the most fundamental unit of information output by a switching device within a CPU. Exergetic thermal, informational and efficiency values are calculated and plotted for our particular CPU, showing how the datasheet standards compare with experimental values. The dissertation concludes with a discussion of the work's significance.
ContributorsHaywood, Anna (Author) / Phelan, Patrick E (Thesis advisor) / Herrmann, Marcus (Committee member) / Gupta, Sandeep (Committee member) / Trimble, Steve (Committee member) / Myhajlenko, Stefan (Committee member) / Arizona State University (Publisher)
Created2014
Description
A P-value based method is proposed for statistical monitoring of various types of profiles in phase II. The performance of the proposed method is evaluated by the average run length criterion under various shifts in the intercept, slope and error standard deviation of the model. In our proposed approach, P-values are computed at each level within a sample. If at least one of the P-values is less than a pre-specified significance level, the chart signals out-of-control. The primary advantage of our approach is that only one control chart is required to monitor several parameters simultaneously: the intercept, slope(s), and the error standard deviation. A comprehensive comparison of the proposed method and the existing KMW-Shewhart method for monitoring linear profiles is conducted. In addition, the effect that the number of observations within a sample has on the performance of the proposed method is investigated. The proposed method was also compared to the T^2 method discussed in Kang and Albin (2000) for multivariate, polynomial, and nonlinear profiles. A simulation study shows that overall the proposed P-value method performs satisfactorily for different profile types.
ContributorsAdibi, Azadeh (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie (Thesis advisor) / Li, Jing (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
Description
In engineering, buckling is mechanical instability of walls or columns under compression and usually is a problem that engineers try to prevent. In everyday life buckles (wrinkles) on different substrates are ubiquitous -- from human skin to a rotten apple they are a commonly observed phenomenon. It seems that buckles with macroscopic wavelengths are not technologically useful; over the past decade or so, however, thanks to the widespread availability of soft polymers and silicone materials micro-buckles with wavelengths in submicron to micron scale have received increasing attention because it is useful for generating well-ordered periodic microstructures spontaneously without conventional lithographic techniques. This thesis investigates the buckling behavior of thin stiff films on soft polymeric substrates and explores a variety of applications, ranging from optical gratings, optical masks, energy harvest to energy storage. A laser scanning technique is proposed to detect micro-strain induced by thermomechanical loads and a periodic buckling microstructure is employed as a diffraction grating with broad wavelength tunability, which is spontaneously generated from a metallic thin film on polymer substrates. A mechanical strategy is also presented for quantitatively buckling nanoribbons of piezoelectric material on polymer substrates involving the combined use of lithographically patterning surface adhesion sites and transfer printing technique. The precisely engineered buckling configurations provide a route to energy harvesters with extremely high levels of stretchability. This stiff-thin-film/polymer hybrid structure is further employed into electrochemical field to circumvent the electrochemically-driven stress issue in silicon-anode-based lithium ion batteries. It shows that the initial flat silicon-nanoribbon-anode on a polymer substrate tends to buckle to mitigate the lithiation-induced stress so as to avoid the pulverization of silicon anode. Spontaneously generated submicron buckles of film/polymer are also used as an optical mask to produce submicron periodic patterns with large filling ratio in contrast to generating only ~100 nm edge submicron patterns in conventional near-field soft contact photolithography. This thesis aims to deepen understanding of buckling behavior of thin films on compliant substrates and, in turn, to harness the fundamental properties of such instability for diverse applications.
ContributorsMa, Teng (Author) / Jiang, Hanqing (Thesis advisor) / Yu, Hongyu (Committee member) / Yu, Hongbin (Committee member) / Poon, Poh Chieh Benny (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Structural integrity is an important characteristic of performance for critical components used in applications such as aeronautics, materials, construction and transportation. When appraising the structural integrity of these components, evaluation methods must be accurate. In addition to possessing capability to perform damage detection, the ability to monitor the level of damage over time can provide extremely useful information in assessing the operational worthiness of a structure and in determining whether the structure should be repaired or removed from service. In this work, a sequential Bayesian approach with active sensing is employed for monitoring crack growth within fatigue-loaded materials. The monitoring approach is based on predicting crack damage state dynamics and modeling crack length observations. Since fatigue loading of a structural component can change while in service, an interacting multiple model technique is employed to estimate probabilities of different loading modes and incorporate this information in the crack length estimation problem. For the observation model, features are obtained from regions of high signal energy in the time-frequency plane and modeled for each crack length damage condition. Although this observation model approach exhibits high classification accuracy, the resolution characteristics can change depending upon the extent of the damage. Therefore, several different transmission waveforms and receiver sensors are considered to create multiple modes for making observations of crack damage. Resolution characteristics of the different observation modes are assessed using a predicted mean squared error criterion and observations are obtained using the predicted, optimal observation modes based on these characteristics. Calculation of the predicted mean square error metric can be computationally intensive, especially if performed in real time, and an approximation method is proposed. With this approach, the real time computational burden is decreased significantly and the number of possible observation modes can be increased. Using sensor measurements from real experiments, the overall sequential Bayesian estimation approach, with the adaptive capability of varying the state dynamics and observation modes, is demonstrated for tracking crack damage.
ContributorsHuff, Daniel W (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Kovvali, Narayan (Committee member) / Chakrabarti, Chaitali (Committee member) / Chattopadhyay, Aditi (Committee member) / Arizona State University (Publisher)
Created2013
Description
Increasing interest in individualized treatment strategies for prevention and treatment of health disorders has created a new application domain for dynamic modeling and control. Standard population-level clinical trials, while useful, are not the most suitable vehicle for understanding the dynamics of dosage changes to patient response. A secondary analysis of intensive longitudinal data from a naltrexone intervention for fibromyalgia examined in this dissertation shows the promise of system identification and control. This includes datacentric identification methods such as Model-on-Demand, which are attractive techniques for estimating nonlinear dynamical systems from noisy data. These methods rely on generating a local function approximation using a database of regressors at the current operating point, with this process repeated at every new operating condition. This dissertation examines generating input signals for data-centric system identification by developing a novel framework of geometric distribution of regressors and time-indexed output points, in the finite dimensional space, to generate sufficient support for the estimator. The input signals are generated while imposing “patient-friendly” constraints on the design as a means to operationalize single-subject clinical trials. These optimization-based problem formulations are examined for linear time-invariant systems and block-structured Hammerstein systems, and the results are contrasted with alternative designs based on Weyl's criterion. Numerical solution to the resulting nonconvex optimization problems is proposed through semidefinite programming approaches for polynomial optimization and nonlinear programming methods. It is shown that useful bounds on the objective function can be calculated through relaxation procedures, and that the data-centric formulations are amenable to sparse polynomial optimization. In addition, input design formulations are formulated for achieving a desired output and specified input spectrum. Numerical examples illustrate the benefits of the input signal design formulations including an example of a hypothetical clinical trial using the drug gabapentin. In the final part of the dissertation, the mixed logical dynamical framework for hybrid model predictive control is extended to incorporate a switching time strategy, where decisions are made at some integer multiple of the sample time, and manipulation of only one input at a given sample time among multiple inputs. These are considerations important for clinical use of the algorithm.
ContributorsDeśapāṇḍe, Sunīla (Author) / Rivera, Daniel E. (Thesis advisor) / Peet, Matthew M. (Committee member) / Si, Jennie (Committee member) / Tsakalis, Konstantinos S. (Committee member) / Arizona State University (Publisher)
Created2014
Description
The activity-based approach to travel demand analysis and modeling, which has been developed over the past 30 years, has received tremendous success in transportation planning and policy analysis issues, capturing the multi-way joint relationships among socio-demographic, economic, land use characteristics, activity participation, and travel behavior. The development of synthesizing population with an array of socio-demographic and socio-economic attributes has drawn remarkable attention due to privacy and cost constraints in collecting and disclosing full scale data. Although, there has been enormous progress in producing synthetic population, there has been less progress in the development of population evolution modeling arena to forecast future year population. The objective of this dissertation is to develop a well-structured full-fledged demographic evolution modeling system, capturing migration dynamics and evolution of person level attributes, introducing the concept of new household formations and apprehending the dynamics of household level long-term choices over time. A comprehensive study has been conducted on demography, sociology, anthropology, economics and transportation engineering area to better understand the dynamics of evolutionary activities over time and their impacts in travel behavior. This dissertation describes the methodology and the conceptual framework, and the development of model components. Demographic, socio-economic, and land use data from American Community Survey, National Household Travel Survey, Census PUMS, United States Time Series Economic Dynamic data and United States Center for Disease Control and Prevention have been used in this research. The entire modeling system has been implemented and coded using programming language to develop the population evolution module named `PopEvol' into a computer simulation environment. The module then has been demonstrated for a portion of Maricopa County area in Arizona to predict the milestone year population to check the accuracy of forecasting. The module has also been used to evolve the base year population for next 15 years and the evolutionary trend has been investigated.
ContributorsPaul, Sanjay (Author) / Pendyala, Ram M. (Thesis advisor) / Kaloush, Kamil (Committee member) / Ahn, Soyoung (Committee member) / Arizona State University (Publisher)
Created2014
Description
Monitoring of air pollutants is critical for many applications and studies. In
order to access air pollutants with high spatial and temporal resolutions, it is
necessary to develop an affordable, small size and weight, low power, high
sensitivity and selectivity, and wireless enable device that can provide real time
monitoring of air pollutants. Three different kind of such devices are presented, they
are targeting environmental pollutants such as volatile organic components (VOCs),
nitrogen dioxide (NO2) and ozone. These devices employ innovative detection
methods, such as quartz crystal tuning fork coated with molecularly imprinted
polymer and chemical reaction induced color change colorimetric sensing. These
portable devices are validated using the gold standards in the laboratory, and their
functionality and capability are proved during the field tests, make them great tools
for various air quality monitoring applications.
order to access air pollutants with high spatial and temporal resolutions, it is
necessary to develop an affordable, small size and weight, low power, high
sensitivity and selectivity, and wireless enable device that can provide real time
monitoring of air pollutants. Three different kind of such devices are presented, they
are targeting environmental pollutants such as volatile organic components (VOCs),
nitrogen dioxide (NO2) and ozone. These devices employ innovative detection
methods, such as quartz crystal tuning fork coated with molecularly imprinted
polymer and chemical reaction induced color change colorimetric sensing. These
portable devices are validated using the gold standards in the laboratory, and their
functionality and capability are proved during the field tests, make them great tools
for various air quality monitoring applications.
ContributorsChen, Cheng, Ph.D (Author) / Tao, Nongjian (Thesis advisor) / Kiaei, Sayfe (Committee member) / Zhang, Yanchao (Committee member) / Tsow, Tsing (Committee member) / Arizona State University (Publisher)
Created2014
Description
The ocean is vital to the health of our planet but remains virtually unexplored. Many researchers seek to understand a wide range of geological and biological phenomena by developing technologies which enable exploration of the deep-sea. The task of developing a technology which can withstand extreme pressure and temperature gradients in the deep ocean is not trivial. Of these technologies, underwater vehicles were developed to study the deep ocean, but remain large and expensive to manufacture. I am proposing the development of cost efficient miniaturized underwater vehicle (mUV) with propulsion systems to carry small measurement devices and enable deep-sea exploration. These mUV's overall size is optimized based on the vehicle parameters such as energy density, desired velocity, swimming time and propulsion performance. However, there are limitations associated with the size of the mUV which leads to certain challenges. For example, 2000 m below the sea level, the pressure is as high as 3000 psi. Therefore, certain underwater vehicle modules, such as the propulsion system, will require pressure housing to ensure the functionality of the thrust generation. In the case of a mUV swimming against the deep-sea current, a thrust magnitude is required to enable the vehicle to overcome the ocean current speed and move forward. Therefore, the size of the mUV is limited by the energy density and the propeller size. An equation is derived to miniaturize underwater vehicle while performing with a certain specifications. An inrunner three-phase permanent magnet brushless DC motor is designed and fabricated with a specific size to fit inside the mUV's core. The motor is composed of stator winding in a pressure housing and an open to water ring-propeller rotor magnet. Several ring-propellers are 3D printed and tested experimentally to determine their performances and efficiencies. A planer motion optimal trajectory for the mUV is determined to minimize the energy usage. Those studies enable the design of size optimized underwater vehicle with propulsion to carry small measurement sensors and enable underwater exploration. Developing mUV's will enable ocean exploration that can lead to significant scientific discoveries and breakthroughs that will solve current world health and environmental problems.
ContributorsMerza, Saeed A (Author) / Meldrum, Deirdre R (Thesis advisor) / Chao, Shih-hui (Committee member) / Shankar, Praveen (Committee member) / Saripalli, Srikanth (Committee member) / Berman, Spring Melody (Committee member) / Arizona State University (Publisher)
Created2014
Description
Organic light emitting diodes (OLEDs) are a promising approach for display and solid state lighting applications. However, further work is needed in establishing the availability of efficient and stable materials for OLEDs with high external quantum efficiency's (EQE) and high operational lifetimes. Recently, significant improvements in the internal quantum efficiency or ratio of generated photons to injected electrons have been achieved with the advent of phosphorescent complexes with the ability to harvest both singlet and triplet excitons. Since then, a variety of phosphorescent complexes containing heavy metal centers including Os, Ni, Ir, Pd, and Pt have been developed. Thus far, the majority of the work in the field has focused on iridium based complexes. Platinum based complexes, however, have received considerably less attention despite demonstrating efficiency's equal to or better than their iridium analogs. In this study, a series of OLEDs implementing newly developed platinum based complexes were demonstrated with efficiency's or operational lifetimes equal to or better than their iridium analogs for select cases.
In addition to demonstrating excellent device performance in OLEDs, platinum based complexes exhibit unique photophysical properties including the ability to form excimer emission capable of generating broad white light emission from a single emitter and the ability to form narrow band emission from a rigid, tetradentate molecular structure for select cases. These unique photophysical properties were exploited and their optical and electrical properties in a device setting were elucidated.
Utilizing the unique properties of a tridentate Pt complex, Pt-16, a highly efficient white device employing a single emissive layer exhibited a peak EQE of over 20% and high color quality with a CRI of 80 and color coordinates CIE(x=0.33, y=0.33). Furthermore, by employing a rigid, tetradentate platinum complex, PtN1N, with a narrow band emission into a microcavity organic light emitting diode (MOLED), significant enhancement in the external quantum efficiency was achieved. The optimized MOLED structure achieved a light out-coupling enhancement of 1.35 compared to the non-cavity structure with a peak EQE of 34.2%. In addition to demonstrating a high light out-coupling enhancement, the microcavity effect of a narrow band emitter in a MOLED was elucidated.
In addition to demonstrating excellent device performance in OLEDs, platinum based complexes exhibit unique photophysical properties including the ability to form excimer emission capable of generating broad white light emission from a single emitter and the ability to form narrow band emission from a rigid, tetradentate molecular structure for select cases. These unique photophysical properties were exploited and their optical and electrical properties in a device setting were elucidated.
Utilizing the unique properties of a tridentate Pt complex, Pt-16, a highly efficient white device employing a single emissive layer exhibited a peak EQE of over 20% and high color quality with a CRI of 80 and color coordinates CIE(x=0.33, y=0.33). Furthermore, by employing a rigid, tetradentate platinum complex, PtN1N, with a narrow band emission into a microcavity organic light emitting diode (MOLED), significant enhancement in the external quantum efficiency was achieved. The optimized MOLED structure achieved a light out-coupling enhancement of 1.35 compared to the non-cavity structure with a peak EQE of 34.2%. In addition to demonstrating a high light out-coupling enhancement, the microcavity effect of a narrow band emitter in a MOLED was elucidated.
ContributorsEcton, Jeremy David (Author) / Li, Jian (Thesis advisor) / Adams, James (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2014