Matching Items (104)
Description
There is a need in the ecology literature to have a discussion about the fundamental theories from which population dynamics arises. Ad hoc model development is not uncommon in the field often as a result of a need to publish rapidly and frequently. Ecologists and statisticians like Robert J. Steidl and Kenneth P Burnham have called for a more deliberative approach they call "hard thinking". For example, the phenomena of population growth can be captured by almost any sigmoid function. The question of which sigmoid function best explains a data set cannot be answered meaningfully by statistical regression since that can only speak to the validity of the shape. There is a need to revisit enzyme kinetics and ecological stoichiometry to properly justify basal model selection in ecology. This dissertation derives several common population growth models from a generalized equation. The mechanistic validity of these models in different contexts is explored through a kinetic lens. The behavioral kinetic framework is then put to the test by examining a set of biologically plausible growth models against the 1968-1995 elk population count data for northern Yellowstone. Using only this count data, the novel Monod-Holling growth model was able to accurately predict minimum viable population and life expectancy despite both being exogenous to the model and data set. Lastly, the elk/wolf data from Yellowstone was used to compare the validity of the Rosenzweig-MacArthur and Arditi-Ginzburg models. They both were derived from a more general model which included both predator and prey mediated steps. The Arditi-Ginzburg model was able to fit the training data better, but only the Rosenzweig-MacArthur model matched the validation data. Accounting for animal sexual behavior allowed for the creation of the Monod-Holling model which is just as simple as the logistic differential equation but provides greater insights for conservation purposes. Explicitly acknowledging the ethology of wolf predation helps explain the differences in predictive performances by the best fit Rosenzweig-MacArthur and Arditi-Ginzburg models. The behavioral kinetic framework has proven to be a useful tool, and it has the ability to provide even further insights going forward.
ContributorsPringle, Jack Andrew McCracken (Author) / Anderies, John M (Thesis advisor) / Kuang, Yang (Committee member) / Milner, Fabio (Committee member) / Arizona State University (Publisher)
Created2022
Description
Ecology has been an actively studied topic recently, along with the rapid development of human microbiota-based technology. Scientists have made remarkable progress using bioinformatics tools to identify species and analyze composition. However, a thorough understanding of interspecies interactions of microbial ecosystems is still lacking, which has been a significant obstacle in the further development of related technologies. In this work, a genetic circuit design principle with synthetic biology approaches is developed to form two-strain microbial consortia with different inter-strain interactions. The microbial systems are well-defined and inducible. Co-culture experiment results show that our microbial consortia behave consistently with previous ecological knowledge and thus serves as excellent model systems to simulate ecosystems with similar interactions. Colony patterns also emerge when co-culturing multiple species on solid media. With the engineered microbial consortia, image-processing based methods were developed to quantify the shape of co-culture colonies and distinguish microbial consortia with different interactions. Factors that affect the population ratios were identified through induction and variations in the inoculation process. Further time-lapse experiments revealed the basic rules of colony growth, composition variation, patterning, and how spatial factors impact the co-culture colony.
ContributorsChen, Xingwen (Author) / Wang, Xiao (Thesis advisor) / Kuang, Yang (Committee member) / Tian, Xiaojun (Committee member) / Brafman, David (Committee member) / Plaisier, Christopher (Committee member) / Arizona State University (Publisher)
Created2022
Description
Complex perovskite materials, including Ba(Zn1/3Ta2/3)O3 (BZT), are commonly used to make resonators and filters in communication systems because of their low dielectric loss and high-quality factors (Q). Transition metal additives are introduced (i.e., Ni2+, Co2+, Mn2+) to act as sintering agents and tune their temperature coefficient to zero or near-zero. However, losses in these commercial dielectric materials at cryogenic temperatures increase markedly due to spin-excitation resulting from the presence of paramagnetic defects. Applying a large magnetic field (e.g., 5 Tesla) quenches these losses and has allowed the study of other loss mechanisms present at low temperatures. Work was performed on Fe3+ doped LaAlO3. At high magnetic fields, the residual losses versus temperature plots exhibit Debye peaks at ~40 K, ~75 K, and ~215 K temperature and can be tentatively associated with defect reactions O_i^x+V_O^x→O_i^'+V_O^•, Fe_Al^x+V_Al^"→Fe_Al^'+V_Al^' and Al_i^x+Al_i^(••)→〖2Al〗_i^•, respectively. Peaks in the loss tangent versus temperature graph of Zn-deficient BZT indicate a higher concentration of defects and appear to result from conduction losses.Guided by the knowledge gained from this study, a systematic study to develop high-performance microwave materials for ultra-high performance at cryogenic temperatures was performed. To this end, the production and characterization of perovskite materials that were either undoped or contained non-paramagnetic additives were carried out. Synthesis of BZT ceramic with over 98% theoretical density was obtained using B2O3 or BaZrO3 additives. At 4 K, the highest Q x f product of 283,000 GHz was recorded for 5% BaZrO3 doped BZT.
A portable, inexpensive open-air spectrometer was designed, built, and tested to make the electron paramagnetic resonance (EPR) technique more accessible for high-school and university lab instruction. In this design, the sample is placed near a dielectric resonator and does not need to be enclosed in a cavity, as is used in commercial EPR spectrometers. Permanent magnets used produce fields up to 1500 G, enabling EPR measurements up to 3 GHz.
ContributorsGajare, Siddhesh Girish (Author) / Newman, Nathan (Thesis advisor) / Alford, Terry (Committee member) / Tongay, Sefaattin (Committee member) / Chamberlin, Ralph (Committee member) / Arizona State University (Publisher)
Created2022
Description
The mutual inhibition between synthetic gene circuits and cell growth produces growth feedback in the host-circuit system. Previous studies have demonstrated that the growth feedback has an marked impact on the molecular dynamics of the host-circuit system. However, the complexity of the growth feedback effect is not fully understood. A theoretical framework was developed to study the dynamics of the coupling between growth feedback and synthetic gene circuits. The study’s results reveal three major points about the impact of growth feedback. First, a nonlinear emergent behavior mediated by growth feedback. The unexpected behavior depends on the dynamic ribosome allocation between gene circuit expression and host cell growth. Second, the emergence and loss of unexpected qualitative states on the host-circuit system generated by ultrasensitive growth feedback. Third, the growth feedback-induced cooperativity behavior in synthetic gene modules competing for resources. In addition, growth feedback attenuated the winner-takes-all rules on resource competition between the two self-activating modules. These results demonstrate that growth feedback plays an important role in the host-circuit system’s molecular dynamics. Characterizing general principles from the effect of growth facilitates the ability to minimize or even harness unexpected gene expression behaviors derived from the effect of growth feedback.
ContributorsMelendez-Alvarez, Juan Ramon (Author) / Tian, Xiaojun (Thesis advisor) / Wang, Xiao (Committee member) / Kuang, Yang (Committee member) / Arizona State University (Publisher)
Created2022
Description
Many important technologies, including electronics, computing, communications, optoelectronics, and sensing, are built on semiconductors. The band gap is a crucial factor in determining the electrical and optical properties of semiconductors. Beyond graphene, newly found two-dimensional (2D) materials have semiconducting bandgaps that range from the ultraviolet in hexagonal boron nitride to the terahertz and mid-infrared in bilayer graphene and black phosphorus, visible in transition metal dichalcogenides (TMDs). These 2D materials were shown to have highly controllable bandgaps which can be controlled by alloying. Only a small number of TMDs and monochalcogenides have been alloyed, though, because alloying compromised the material's Van der Waals (Vdw) property and the stability of the host crystal lattice phase. Phase transition in 2D materials is an interesting phenomenon where work has been done only on few TMDs namely MoTe2, MoS2, TaS2 etc.In order to change the band gaps and move them towards the UV (ultraviolet) and IR (infrared) regions, this work has developed new 2D alloys in InSe by alloying them with S and Te at 10% increasing concentrations. As the concentration of the chalcogens (S and Te) increased past a certain point, a structural phase transition in the alloys was observed. However, pinpointing the exact concentration for phase change and inducing phase change using external stimuli will be a thing of the future. The resulting changes in the crystal structure and band gap were characterized using some basic characterization techniques like scanning electron microscopy (SEM), X-ray Diffraction (XRD), Raman and photoluminescence spectroscopy.
ContributorsYarra, Anvesh Sai (Author) / Tongay, Sefaattin (Thesis advisor) / Yang, Sui (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2022
Description
Thin film solar cells are based on polycrystalline materials that contain a high concentration of intrinsic and extrinsic defects. Improving the device efficiency in such systems relies on understanding the nature of defects - whether they are positive, negative, or neutral in their influence - and their sources in order to engineer optimized absorbers. Oftentimes, these are studied individually, as characterization techniques are limited in their ability to directly relate material properties in individual layers to their impact on the actual device performance. Expanding the tools available for increased understanding of materials and devices has been critical for reducing the translation time of laboratory-scale research to changes in commercial module manufacturing lines. The use of synchrotron X-ray fluorescence (XRF) paired with X-ray beam induced current and voltage (XBIC, XBIV respectively) has proven to be an effective technique for understanding the impact of material composition and inhomogeneity on solar cell device functioning. The combination of large penetration depth, small spot size, and high flux allows for the measurement of entire solar cell stacks with high spatial resolution and chemical sensitivity. In this work, I combine correlative XRF/XBIC/XBIV with other characterization approaches across varying length scales, such as micro-Raman spectroscopy and photoluminescence, to understand how composition influences device performance in thin films. The work described here is broken into three sections. Firstly, understanding the influence of KF post-deposition treatment (PDT) and the use of Ag-alloying to reduce defect density in the Ga-free material system, CuInSe2 (CIS). Next, applying a similar characterization workflow to industrially relevant Ga-containing Cu(In1-xGax)Se2 (CIGS) modules with Ag and KF-PDT. The influence of light soaking and dark heat exposure on the modules are also studied in detail. Results show that Ag used with KF-PDT in CIS causes undesirable cation ordering at the CdS interface and affects the device through increased potential fluctuations. The results also demonstrate the importance of tuning the concentration of KF-PDT used when intended to be used in Ag-alloyed devices. Commercially-processed modules with optimized Ag and KF concentrations are shown to have the device performance instead be dominated by variations in the CIGS composition itself. In particular, changes in Cu and Se concentrations are found to be most influential on the device response to accelerated stressors such as dark heat exposure and light soaking. In the final chapter, simulations of nano-scale XBIC and XBIV are done to contribute to the understanding of these measurements.
ContributorsNietzold, Tara (Author) / Bertoni, Mariana I. (Thesis advisor) / Holt, Martin (Committee member) / Shafarman, William N. (Committee member) / Tongay, Sefaattin (Committee member) / Arizona State University (Publisher)
Created2021
Description
The representation of a patient’s characteristics as the parameters of a model is a key component in many studies of personalized medicine, where the underlying mathematical models are used to describe, explain, and forecast the course of treatment. In this context, clinical observations form the bridge between the mathematical frameworks and applications. However, the formulation and theoretical studies of the models and the clinical studies are often not completely compatible, which is one of the main obstacles in the application of mathematical models in practice. The goal of my study is to extend a mathematical framework to model prostate cancer based mainly on the concept of cell-quota within an evolutionary framework and to study the relevant aspects for the model to gain useful insights in practice. Specifically, the first aim is to construct a mathematical model that can explain and predict the observed clinical data under various treatment combinations. The second aim is to find a fundamental model structure that can capture the dynamics of cancer progression within a realistic set of data. Finally, relevant clinical aspects such as how the patient's parameters change over the course of treatment and how to incorporate treatment optimization within a framework of uncertainty quantification, will be examined to construct a useful framework in practice.
ContributorsPhan, Tin (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J (Committee member) / Crook, Sharon (Committee member) / Maley, Carlo (Committee member) / Bryce, Alan (Committee member) / Arizona State University (Publisher)
Created2021
Description
Synthetic biology (SB) has become an important field of science focusing on designing and engineering new biological parts and systems, or re-designing existing biological systems for useful purposes. The dramatic growth of SB throughout the past two decades has not only provided us numerous achievements, but also brought us more timely and underexplored problems. In SB's entire history, mathematical modeling has always been an indispensable approach to predict the experimental outcomes, improve experimental design and obtain mechanism-understanding of the biological systems. \textit{Escherichia coli} (\textit{E. coli}) is one of the most important experimental platforms, its growth dynamics is the major research objective in this dissertation. Chapter 2 employs a reaction-diffusion model to predict the \textit{E. coli} colony growth on a semi-solid agar plate under multiple controls. In that chapter, a density-dependent diffusion model with non-monotonic growth to capture the colony's non-linear growth profile is introduced. Findings of the new model to experimental data are compared and contrasted with those from other proposed models. In addition, the cross-sectional profile of the colony are computed and compared with experimental data. \textit{E. coli} colony is also used to perform spatial patterns driven by designed gene circuits. In Chapter 3, a gene circuit (MINPAC) and its corresponding pattern formation results are presented. Specifically, a series of partial differential equation (PDE) models are developed to describe the pattern formation driven by the MINPAC circuit. Model simulations of the patterns based on different experimental conditions and numerical analysis of the models to obtain a deeper understanding of the mechanisms are performed and discussed. Mathematical analysis of the simplified models, including traveling wave analysis and local stability analysis, is also presented and used to explore the control strategies of the pattern formation. The interaction between the gene circuit and the host \textit{E. coli} may be crucial and even greatly affect the experimental outcomes. Chapter 4 focuses on the growth feedback between the circuit and the host cell under different nutrient conditions. Two ordinary differential equation (ODE) models are developed to describe such feedback with nutrient variation. Preliminary results on data fitting using both two models and the model dynamical analysis are included.
ContributorsHe, Changhan (Author) / Kuang, Yang (Thesis advisor) / Wang, Xiao (Committee member) / Kostelich, Eric (Committee member) / Tian, Xiaojun (Committee member) / Gumel, Abba (Committee member) / Arizona State University (Publisher)
Created2021
Description
The application of silicon thin films in solar cells has evolved from their use in amorphous silicon solar cells to their use as passivating and carrier-selective contacts in crystalline silicon solar cells. Their use as carrier-selective contacts has enabled crystalline silicon solar cell efficiencies above 26%, just 3% shy of the theoretical efficiency limit. The two cell architectures that have exceeded 26% are the silicon heterojunction and tunnel oxide passivating contact cell. These two cell architectures use two different forms of silicon thin films. In the case of the silicon heterojunction, the crystalline wafer is sandwiched between layers of intrinsic amorphous silicon, which acts as the passivation layer, and doped amorphous silicon, which acts as the carrier-selective layer. On the other hand, the tunnel oxide passivating contact cell uses a thin silicon oxide passivation layer and a doped polycrystalline silicon layer as the carrier-selective layer. Both cell structures have their distinct advantages and disadvantages when it comes to production. The processing of the silicon heterojunction relies on a low thermal budget and leads to high open-circuit voltages, but the cost of high-vacuum processing equipment presents a major hurdle for industrial scale production while the tunnel oxide passivating contact can be easily integrated into current industrial lines, yet it requires a higher thermal budgets and does not produce as high of an open-circuit voltage as the silicon heterojunction. This work focuses on using both forms of silicon thin films applied as passivating and carrier-selective contacts to crystalline silicon thin films.First, a thorough analysis of the series resistivity in silicon heterojunction solar cells is conducted. In particular, variations in the thickness and doping of the individual
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contact layers are performed to reveal their effect on the contact resistivity and in turn the total series resistivity of the cell. Second, a tunnel oxide passivated contact is created using a novel deposition method for the silicon oxide layer. A 21% efficient proof-of-concept device is presented demonstrating the potential of this deposition method. Finally, recommendations to further improve the efficiency of these cells is presented.
ContributorsWeigand, William (Author) / Holman, Zachary (Thesis advisor) / Yu, Zhengshan (Committee member) / Bertoni, Mariana (Committee member) / Tongay, Sefaattin (Committee member) / Arizona State University (Publisher)
Created2023
Description
Since the 20th century, Arizona has undergone shifts in agricultural practices, driven by urban expansion and crop irrigation regulations. These changes present environmental challenges, altering atmospheric processes and influencing climate dynamics. Given the potential threats of climate change and drought on water availability for agriculture, further modifications in the agricultural landscape are expected. To understand these land use changes and their impact on carbon dynamics, our study quantified aboveground carbon storage in both cultivated and
abandoned agricultural fields. To accomplish this, we employed Python and various geospatial libraries in Jupyter Notebook files, for thorough dataset assembly and visual, quantitative analysis. We focused on nine counties known for high cultivation levels, primarily located in the lower latitudes of Arizona. Our analysis investigated carbon dynamics across not only abandoned and actively cultivated croplands but also neighboring uncultivated land, for which we estimated the extent. Additionally, we compared these trends with those observed in developed land areas.
The findings revealed a hierarchy in aboveground carbon storage, with currently cultivated lands having the lowest levels, followed by abandoned croplands and uncultivated wilderness. However, wilderness areas exhibited significant variation in carbon storage by county compared to cultivated and abandoned lands. Developed lands ranked highest in aboveground carbon storage, with the median value being the highest. Despite county-wide variations, abandoned croplands generally contained more carbon than currently cultivated areas, with adjacent wilderness lands containing even more than both. This trend suggests that cultivating croplands in the region reduces aboveground carbon stores, while abandonment allows for some replenishment, though only to a limited extent. Enhancing carbon stores in Arizona can be achieved through active restoration efforts on abandoned cropland. By promoting native plant regeneration and boosting aboveground carbon levels, these measures are crucial for improving carbon sequestration. We strongly advocate for implementing this step to facilitate the regrowth of native plants and enhance overall carbon storage in the region.
ContributorsGoodwin, Emily (Author) / Eikenberry, Steffen (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2024-05