Master of Science, The Ohio State University, 2021, Horticulture and Crop Science

Many farmers typically regard wheat as a “low input” crop and expect low yields and low returns. Conversely, some farmers intensively manage wheat with many inputs and expect high yields and returns. The objective of this research was to identify inputs that improve wheat grain yield, straw yield, and economic return and reduce deoxynivalenol (DON) concentration in the grain. An incomplete factorial, omission trial was established at two locations in Ohio (South Charleston and Custar) during the 2019-2020 and 2020-2021 growing seasons. Treatments consisted of intensive management (IM) which received all inputs, a traditional management (TM), and the individual addition or removal each input from the TM or IM, respectively. The inputs were a high seeding rate, a high N rate, a split application of N, a spring sulfur application, a fungicide application at Feekes 9, and a fungicide application at Feekes 10.5.1. Intensive management increased grain yield at three of the site-years during this study by an average of 0.83 Mg ha-1. At the South Charleston location, in general, the use of a fungicide at either timing proved to be important for protecting yield. The addition of a fungicide at Feekes 10.5.1 to the TM significantly protected yield both years by an average of 0.66 Mg ha-1 and the removal of this fungicide from the IM significantly decreased yield by 0.63 Mg ha-1 in 2021. Additionally, at the same location the addition of a fungicide at Feekes 9 to the TM and the removal of a fungicide from the IM significantly changed yield in 2020 by 0.81 and -0.71 Mg ha-1. At Custar, only one treatment significantly changed yield in either year. In 2021, the removal of split N from the IM significantly reduced grain yield by 0.44 Mg ha-1. Straw yield was not consistently affected by any treatment in this study. DON concentration was significantly reduced by the IM at South Charleston both years due to the addition of a fungicide at Feekes 10.5.1. Intensive management did not (open full item for complete abstract)

Committee: Laura Lindsey (Advisor); Pierce Paul (Committee Member); Tim Haab (Committee Member) Subjects: Agricultural Economics; Agriculture; Agronomy

PHD, Kent State University, 2011, College of Arts and Sciences / Department of Geography

Corn and soybean yield maps derived from yield monitors can be applied for precision agricultural practices by using them to develop or help develop management zones (field areas managed homogeneously). Applying variable fertilizer rates to zones based on need has been shown to increase profits, in part, due to less fertilizer being used than with uniform application. This can have environmental benefits by resulting in less run-off or leaching of fertilizer into the hydrologic system. Many corn and soybean farmers do not have yield monitors to produce yield maps. To help resolve this problem, this research focuses on predicting corn and soybean yield at the field scale. Corn and soybean yield monitor data were acquired and cleaned by different methods to develop better data to base predictions on. Correlations between different Landsat-derived values and corn or soy yield at different growth stages were made. Artificial neural networks (ANN) models based on four independent variables were developed to predict yield and results were compared to multiple linear regression (MLR). Yield cleaning methods that included median neighborhood statistics processing produced better data. Landsat correlations with soybean yield were most reliably high when solely using band 4 during much of the reproductive stage (R²=0.63) while corn yield was better predicted during later vegetative stages. Many different indices proved useful to predict corn, with soil-adjusted vegetation indices having the highest correlations (R² ranging from 0.60 to 0.62). Overall, it was shown that Landsat can predict yield better and, hence, sense crop condition better at distinctly different times of the season for corn and soybeans. ANN predicted yield slightly better than MLR, having an R² value 0.03 higher and increased the R² value with the Landsat crop condition variable by 0.115. Additionally, a Landsat-based county corn yield prediction model that included imagery from the end of July to the latt (open full item for complete abstract)

Committee: Mandy Munro-Stasiuk (Advisor); Scott Sheridan (Committee Member); Emariana Taylor (Committee Member); Joseph Ortiz (Committee Member); Murali Shanker (Committee Member) Subjects: Agriculture; Geographic Information Science; Remote Sensing

Master of Science, The Ohio State University, 2016, Food, Agricultural and Biological Engineering

With the rising cost of inputs and the shrinking profit margins in agriculture, farmers are looking to manage at the plant level to increase crop yields. As the physical size of agricultural field machinery continues to grow, many agriculture professionals recognize the negative effects of increasing gross vehicle weights on soil structure, health and productivity. The persistent trend of increased machinery size and gross weights thus exacerbating soil compaction which reduces crop yields and impacts profitability. This manuscript focuses on assessing the adverse impact of high axle loads on field productivity for corn production. Historically, many studies were performed using axle loads ranging from 10 T to 20 T. Few, if any, studies were conducted at axle loads in excess of 20 T. A better understanding of higher axle loads is needed in view of the trend of increasing equipment size where axle loads now approach 50 T. Development of a compaction model combined with data tools will allow users to process remote sensed imagery and CANbus data to better visualize and estimate the yield-related effects of compaction. The overarching goal of the envisioned tool is to provide farm managers and decision makers with actionable information as they assess the ever-expanding number of equipment options available in the marketplace. By coupling remote sensed imagery, yield monitor data, CANbus data and field trial results, the envisioned tool aids producers in making informed decisions specific to their equipment complements and soils via information extraction and synthesis from the ever-expanding quantity of data being collected on their farms. This manuscript details a series on investigations undertaken to better understand the potential effects of each pass of machinery over a field. These investigations were designed to: 1) develop an empirical model framework to predict the magnitude of compaction events and the resulting yield penalty based on axle (open full item for complete abstract)

Committee: Scott Shearer Dr. (Advisor); John Fulton Dr. (Committee Member) Subjects: Agricultural Engineering

Master of Science, The Ohio State University, 1967, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 1966, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 2007, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 1961, Graduate School

Committee: Not Provided (Other) Subjects:

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2024, Photochemical Sciences

R-alkoxysilanes are the monomer workhorses of silicon-based sol-gel chemistry and are used as the building blocks for materials from silicas to silicones. However, since their inception, the sol-gel and siloxanes communities have struggled with uncontrolled hydrolysis, premature condensation, and overall polymerization and functionalization control. This dissertation focuses on the development of new silicon sol-gel chemistry methodologies which utilize photocaged R-alkoxysilanes and siloxane polymers to aid in synthetic control towards distinct silicon-based materials. We started our investigation with the synthesis and characterization of 2-nitrobenzyloxy photocage systems from ethyl and phenyl derivatives of Rx-(alkoxy)silanes, with x=0-3 and y=1-4, end group photocaged polydimethylsiloxanes, as well as photocaged polyhedral oligomeric silicon-based cage systems. Furthermore, we have also developed Rx-(alkoxy)silanes, with x=0-3 and y=1-4 that contain the 3-dimethylaminobenzyloxy photocage as a more stable alternative to the 2-nitrobenzyloxy based compounds. We have explored the photochemical responses for photo removal including kinetics, efficiency, stability, and tin catalyzed coupling of products to induce polymerization and surface functionalization. We have found that sufficient removal of the photocage groups was achieved, giving a new avenue to generate silicon-based materials. For this dissertation, Chapter 1 describes the background photochemical and silicon-based chemistries needed to understand these processes and their challenges. Chapter 2 details the extensive work on Rx-(alkoxy)silanes containing 2-nitrobenzyloxy groups and their performance in photochemical processes. Chapter 3 defines the work on 2-nitrobenzyloxy polymeric/oligomeric versions of silicon-based materials. Chapter 4 gives an overview of our preliminary work on 3-dimethylaminobenzyloxy photocaged Rx-(alkoxy)silanes. Finally, Chapter 5 gives conclusions and connections for this resea (open full item for complete abstract)

Committee: Joseph Furgal Ph.D. (Committee Chair); Ellen Gorsevski Ph.D. (Other); Jayaraman Sivaguru Ph.D. (Committee Member); Alexander Tarnovsky Ph.D. (Committee Member) Subjects: Chemistry; Organic Chemistry

Doctor of Philosophy, Case Western Reserve University, 2024, Macromolecular Science and Engineering

Traditionally, extrinsic approaches (e.g. blending and using additives) have been used to enhance the mechanical properties (e.g. toughness) of commercially available semicrystalline thermoplastics. In a continual search for economically scalable, scrapless, simple, and versatile manufacturing approaches, novel solid-state processes have a unique advantage over melt-processing methods alone. Cold-roll milling, or plastically deforming a workpiece by passing it through two counter-rotating rollers below its primary softening temperature, is well-established in the production of ductile metals. Roll-milling not only reduces thickness, but also cold-works the material improving its strength through microstructural refinement. In polymers, a crystalline network structure develops. The focus of this work is on biaxial cold-rolling (cross-rolling) which involves cross-passes alternately 90 ° apart, resulting in a sheet with planar isotropy. In the first part of this dissertation (chapter 2), the deformation of HDPE by cross-rolling is studied. Enhanced barrier properties (measured by oxygen permeability analyzer), increased visible light transmission (measured by spectrophotometer), and increased tensile fracture strength were observed after cross-rolling. A connection to discontinuous change in crystalline structure with thickness reduction (i.e. lamellar fragmentation) detected by density measurement, thermal analysis, and small-angle x-ray scattering (SAXS) is discussed. The second portion (chapters 3-5) focuses on the cross-roll pre-deformation of semicrystalline polymers below both the Tm and Tg at room temperature, and subsequently annealing at temperatures both below and above the Tg. In chapter 3, the Izod impact toughness of poly(p-phenylene sulfide), a notoriously low toughness high-temperature engineering thermoplastic, is found to increase by a factor of 10 after cross-rolling. The elongation to failure is enhanced by a factor of nearly 6 by cross- (open full item for complete abstract)

Committee: Gary Wnek (Committee Chair); Lei Zhu (Committee Member); Ica Manas (Committee Member); John Lewandowski (Committee Member) Subjects: Materials Science; Mechanical Engineering; Mechanics; Plastics

Doctor of Philosophy (PhD), Wright State University, 2023, Environmental Sciences PhD

Successful crop production relies on soils with balanced physical, chemical and biological properties. Demand for greater crop yields has led to the breakdown of soil properties through detrimental agricultural practices. To combat soil degradation, farmers employ field management practices including cover crop application, crop rotation strategies and organic soil amendment addition. These practices, used independently or in combination, can improve soil stability, increase soil nutrient content and functions of beneficial soil microbiota while increasing crop yield. Despite showing promise as an organic soil amendment, dredged sediments are still not well understood, due in part to the fresh or weathered conditions dredged sediments can be applied. Specifically, there is currently no research combining dredged sediments with cover crops, comparing different dredged sediments conditions in a single study or evaluating dredged sediment condition coupled with cropping strategies. To address these knowledge gaps, my dissertation evaluates changes in soil properties and crop responses when dredged sediments are coupled with these practices. I evaluated changes in dredged sediment property responses and corn production following winter rye cover crop application compared to a fallow season in a field experiment where I found cover crop application increased corn yields compared to a fallow season. These differences were driven by microbial-associated nutrient mineralization. Additionally, I quantified soil property and corn responses to different application ratios of fresh and weathered dredged sediments in a greenhouse experiment and determined applications of dredged sediments calculated based on the nutrient recovery ratio are not sufficient to provide benefits to agricultural soils. However, in 100% applications, weathered dredged sediments were more beneficial to corn growth than agricultural soils, while fresh dredged sediments proved detrimental to corn growth. (open full item for complete abstract)

Committee: Megan Rúa Ph.D. (Committee Chair); Silvia Newell Ph.D. (Committee Member); Louise Stevenson Ph.D. (Committee Member); Katie Hossler Ph.D. (Committee Member); Zheng Xu Ph.D. (Committee Member) Subjects: Environmental Science

PhD, University of Cincinnati, 2023, Business: Business Administration

This dissertation consists of three essays studying the cross-section of asset returns using new empirical approaches. In Essay 1, I forecast firm-level expected growth via machine learning and study the relationship between the expected growth and future stock returns. In Essay 2, I study the drivers of stocks' migration across BE/ME portfolios and how the migration affects the value premium. In Essay 3, I study the protection effect on corporate bonds issued by state-owned enterprises. Essay 1: Expected growth is an important firm fundamental variable but is unobservable and difficult to estimate. In this study, I apply machine learning (ML) to forecast growth at the firm level. Compared with conventional linear regression, ML models produce more accurate forecasts out of sample. Among the ML models, non-linear models perform the best. In particular, the gradient boosting regression reduces the mean and median forecast errors by 9.52% and 20.95%, respectively, relative to linear regression. Moreover, the ML-based growth measure exhibits sensible properties at the firm level, in subsamples, and at the aggregate level. Consistent with theory, the firm-level expected growth predicts cross-sectional stock returns positively, controlling for past growth. Firms in the top decile of the expected change in growth beat those in the bottom decile by an average of 0.56% per month (t = 4.49), which cannot be explained by most benchmark models. The aggregate expected change in growth also forecasts stock market returns positively over a period ranging from 24 months to 60 months. Essay 2: In this paper, we revisit the migration of stocks across BE/ME portfolios contributing to the value premium. We seek to address an unanswered question in Fama and French (2007) regarding the underlying drivers of this migration. We investigate whether the movement of stocks is affected by changes in fundamental characteristics or is merely a result of random fluctuations. Our an (open full item for complete abstract)

Committee: Chen Xue Ph.D. (Committee Chair); Yan Yu Ph.D. (Committee Member); Tong Yu Ph.D. (Committee Member); Michael Ferguson Ph.D. (Committee Member) Subjects: Business Administration

Master of Science (MS), Bowling Green State University, 2023, Physics

Colloidal semiconductor nanocrystals (NCs) have been utilized to great effect in optoelectronic applications in the last half-century due to their favorable optical and electronic properties. However, these materials suffer significant performance decline as optical or electrical excitation power increases. The culprit of this decline is the Auger recombination of multiple excitons that produces excess heat from the NC energy. This process poses a significant obstacle to NC performance in photodetectors, X-ray scintillators, lasers, and high-brightness LEDs. A new NC structure, semiconductor quantum shells (QSs) are an emerging NC morphology that solve this problem by providing one of the slowest rates of Auger decay for colloidal NCs yet. These NCs are synthesized in a series of time-dependent injections that layer the desired materials in successive shells. Early iterations of these NCs were still limited by a high rate of surface-trap recombination. Alloying the outer CdS layer with ZnS to produce a CdS-CdSe-CdS-ZnS QS has proven to reduce surface carrier decay. The resulting QSs have photoluminescence quantum yields as high as 90%, and biexciton emission quantum yields as high as 79%. These characteristics make QSs favorable for high-excitation applications when compared to other low-dimensional semiconductors.

Committee: Mikhail Zamkov Ph.D. (Committee Chair); Marco Nardone Ph.D. (Committee Member); Alexey Zayak Ph.D. (Committee Member) Subjects: Materials Science; Physical Chemistry; Physics

Master of Science (MS), Ohio University, 2023, Geography (Arts and Sciences)

This thesis aimed to understand the complex interactions between land-use changes and agricultural production to inform decision-making and maximize crop yields. The research used advanced tools and techniques, including GIS, remote sensing, and spatial modeling, to analyze changes in land cover classes over time. The results showed a significant shift in land cover, with cropland increasing from 43.15% in 2010 to 55.03% in 2016, while grassland decreased from 48.38% in 2010 to 36.69% in 2016. The thesis also explored the impact of environmental factors on maize yields in three Nigerian states, finding that temperature and precipitation was the most sensitive factor influencing yields, and that land cover changes had a moderate influence. The study highlights the importance of using advanced tools and techniques to analyze land use and cover changes and their impact on agricultural production. The findings provide valuable insights for remote sensing and GIS practitioners interested in monitoring land cover and land use changes for natural land preservation, urbanization, agricultural land expansion and sustainability, as well as farmland loss. Furthermore, this thesis demonstrates the importance of considering environmental factors such as temperature, normalized vegetation index, and precipitation alongside land cover changes to better understand the impact of different factors on crop yields. It is recommending the use of both multiple regression models and spatial geographical models to gain a better understanding of how different land cover changes affect crop yields, with the latter providing better results based on AIC and 𝑅2

Committee: Sinha Gaurav (Advisor); Dorothy Sack (Committee Member); Edna Wangui (Committee Member) Subjects: Geographic Information Science; Geography; Remote Sensing

Master of Science, The Ohio State University, 2023, Horticulture and Crop Science

When attempting to maximize soybean yield it is vital to analyze the interactions that occur between planting date and cover crop presence. Research has consistently shown that planting date has the greatest influence on soybean grain yield. However, studies testing for how early soybean can realistically be planted and impacts that may result from such a planting are non-existent. Therefore, the objectives of this study were to 1) determine the yield impact when growing soybean with or without a rye cover crop for three different planting dates and 2) to measure the survivability of soybean seedlings at each planting. A field experiment was conducted at two locations within Ohio in South Charleston and Wooster for the 2021 and 2022 growing seasons. A randomized complete block design was utilized consisting of four replications with nine treatments. The two factors examined were planting date and cover crop presence along with termination timing. Herbicide burndown of the cover crop was coordinated with the planting date of each soybean group. Plant population over time, soil temperature along with percent moisture over time, soybean yield, and rye biomass dry weight were evaluated. Plant populations were between 25% and 42% greater as planting was delayed into May and the best stands were achieved by forgoing a cover crop. However, the treatments with the greatest plant populations planted in May did not result in a yield advantage compared to the plantings in early or late April. When planting ultra-early prior to 15 April, a cover crop proved unnecessary and should be avoided. Planting ultra-early with a cover crop resulted in significant yield declines across both locations of between 24% and 59% compared to planting ultra-early without a cover crop.

Committee: Laura Lindsey (Advisor); Alex Lindsey (Committee Member); Marilia Chiavegato (Committee Member) Subjects: Agriculture; Agronomy

Master of Science, University of Akron, 2023, Geology

In 1967, Wolman modeled how human land-use modification affects sediment yield in the U.S. Middle-Atlantic. This study uses the sediment of Wyoga Lake, Summit County, Ohio to quantify the impacts of land use change on sediment yield, to determine if there is a relationship between land use and the sedimentary heavy metal record, and to test if Wolman's model is applicable to northeast Ohio. Mud Brook flows into and out of Wyoga Lake, thus the lake traps much of the sediment yield from the upper Mud Brook watershed. Based upon wave base models and lakefloor sediment properties, lacustrine sediment accumulates in water deeper than 2.8 m. Sediment cores were collected from deep-water basins and dated by correlating to absolute-dated cores from other Ohio kettle lakes and by using event chrono-stratigraphy to identify lithologic features associated with events of known age. The 266.5 cm-long composite core contains a 220-year environmental history record that was divided into 5 periods of varying human-induced land use change to the Wyoga Lake watershed. The oldest Period, the Pre-Settlement Period (pre-1804) extends from 266.5 to 240.5 cm below lake floor (cmblf) and has organic-rich mud, low Ti concentrations, and a low mass accumulation rate (MAR) of 0.026 g/cm2/yr that accumulated when the forested watershed limited sediment yield. The Settlement and Agriculture Period (240.5─147.6 cmblf; 1804─1964) begins with an initial decline in organic matter followed by elevated arsenic concentrations later in the Period, and a MAR of 0.323 g/cm2/yr which is 12X greater than the Pre─Settlement Period. The sediment properties are interpreted to represent increased terrigenous influx due to deforestation when Stow and Hudson, OH were settled, followed by agricultural activities that applied arsenic-based insecticides to orchards. The Lakeside Housing and Construction Period (147.6 to 94.0 cmblf; 1964─1984) occurred prior to the use of construction-site erosion control practices (open full item for complete abstract)

Committee: John Peck (Advisor); John Senko (Committee Member); Caleb Holyoke (Committee Member) Subjects: Geology; Limnology

Master of Science, The Ohio State University, 2023, Environmental Science

A growing body of scientific literature has identified the potential that conservation agricultural practices can play in improving agroecosystem services, including sequestering carbon and lowering greenhouse gas (GHG) emissions while simultaneously making croplands more productive and resilient to the changing climate. To facilitate the adoption of conservation agricultural practices, farmers need incentives beyond yield. While agriculture companies have recently entered the carbon credit markets, there are a lot of uncertainties regarding the ability to measure and monitor site-specific carbon sequestration and GHG emissions, as well as the potential of agricultural practices to impact soil organic carbon (SOC), crop yield, and GHG emissions due to high degree of spatial and temporal variation that exist in agriculture production systems. Thus, the main objective of this research was to assess the extent to which row-crop production can sequester SOC and reduce GHG emissions while improving crop productivity under current and conservation agricultural practices. To meet the objective, a process-based biogeochemical Denitrification Decomposition (DNDC) model was developed at the HUC-12 subwatershed scale for the Maumee River Watershed (MRW). The model was calibrated, validated, and run from 2000 to 2020 to simulate SOC and GHG emissions under current practices. The model was then run under conservation agricultural practices, including no-tillage, reduced tillage, increased corn residue on field after harvest, and cover crops, and the effectiveness of these practices to improve SOC and corn and soybean yields were compared to the current agricultural practices. The average annual CO2 emissions ranging from 1,945 to 2,357 kg C/ha dominated the Southern and Northwest parts of the watershed while the pocket of areas with high average annual N2O emissions ranging from 3.31 to 11.63 kg N/ha was mostly located in the middle part, Northeast, and Northwest parts of the wa (open full item for complete abstract)

Committee: Sami Khanal (Advisor); Brent Sohngen (Committee Member); Bhavik Bakshi (Committee Member) Subjects: Agriculture; Environmental Science

Doctor of Education , University of Dayton, 2022, Educational Leadership

Student enrollment is one of the key elements of leading schools. Now more than ever, there is an asserted effort to increase representation on college campuses across America. Many predominantly white institutions are strategizing ways to increase the number of Black students on their campuses. While enrollment decisions are ultimately subjective in nature; there are themes across Black student decision processes that can lead school administrators to understanding how they can increase representation. The purpose of this study is to understand the reasons why Black students ultimately decide to not enroll at higher education institutions despite being admitted. The findings reveal the key factors contributing to their decision to not enroll, and how they arrived at their final decision.

Committee: Davin Carr-Chellman (Committee Chair); Thomas Easley (Committee Member); Elizabeth Essex (Committee Member) Subjects: African Americans; Education; Educational Leadership; Higher Education; Higher Education Administration; Organization Theory

Doctor of Education , University of Dayton, 2022, Educational Leadership

There is currently no designated policy, procedure or staff in place to facilitate the objective of increasing student yield. As a result, magnet applications and acceptance of invitations to attend Owl Middle School is approached without a strategy which makes planning difficult and negates the ability to determine effective methods. Filling these public-school magnet seats is a priority as student enrollment equates to staff funding from the state and school doors being open (NCES, 2020). Identifying policy to increase 6th grade magnet students is determined by setting achievable goals. Setting achievable goals for increasing magnet students begins by identifying specific, measurable, achievable, time bound and realistic objectives. Elementary schools with similar demographic populations will be targeted with recruitment efforts through speaking engagements at the schools, parent information nights, and printed material in English and Spanish distributed to prospective families and students. The purpose of this study is to understand the effectiveness of this targeted marketing and to develop a process of continuous improvement thus potentially increasing 6th grade magnet student yield. Two semi-structured virtual interviews consisting of five questions were conducted for 10 families regarding their decision of school choice and the impact marketing had. Findings included a need to incorporate digital marketing along with honoring the power of student decision making in this school choice process.

Committee: Davin Carr-Chellman Ph.D. (Committee Chair) Subjects: Black Studies; Education; Education Policy; Educational Leadership; Educational Theory; Multicultural Education; Pedagogy; School Administration; Teacher Education; Teaching

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2022, Photochemical Sciences

Our overall goal here in this dissertation is to develop silicon-based hybrid materials that are potential high stability materials replacements for those in current electronics systems. To design the hybrid structures, a unique class of silicon-based compounds, silsesquioxanes (SQ) was used as the building block. SQs are three dimensionally compact Si-O bonded, cage-type compounds that can be synthesized to contain a variety of functional groups on each of the cage vertices. They offer useful properties such as thermal and photo stability, a high degree of functionalization, solution processability, and facile synthesis. The works in this dissertation focus on mixed functional (vinyl/phenyl) SQs of different sized cages containing 8, 10, and 12 silicon atoms. They are synthesized by fluoride catalyzed rearrangement reaction in a statistically controlled manner to achieve the desired vinyl groups for oligomerization. Spectroscopic measurements in picosecond/subpicosecond timeframes were performed before evaluating their potential applications. In chapter 2, vinyl/phenylSQs are cross-coupled by 4-di-bromo-aromatic linkers: Benzothiadiazole (BT), Phenanthrenequinone (PQ), Ethyl-carbazole (EC) and Phenyl-carbazole (PC). To compare photophysical properties between caged and non-caged structures, bis-tri-alkoxysilyl (linker) model compounds are synthesized. Luminescence quantum yields for oligomers are generally lower than the corresponding model compounds (except for PQ) which denotes non-radiative energy transfer possibility in oligomer. In addition, rapid transient absorption anisotropy decay (10's ps in oligomers) provide signatures for excitation energy transfer between linker chromophores in oligomers. In chapter 3, we have designed hybrid oligomers with a vinyl/phenylSQ cage backbone linked with cross-linkers including 2,7-dibromo-9-fluorenone, 2,7-dibromo-9,9-dimethylfluorene, 1,4-dibromo-2,5-dimethoxybenzene, 2,5-dibromopyridine, 2,6-dibromopyridine, 2, (open full item for complete abstract)

Committee: Joseph Furgal Ph.D. (Committee Chair); Robyn Miller Ph.D. (Other); H. Peter Lu Ph.D. (Committee Member); Xiaohong Tan Ph.D. (Committee Member) Subjects: Organic Chemistry; Physical Chemistry

Master of Science, The Ohio State University, 2022, Environment and Natural Resources

Oil and natural gas pipelines are essential to the transport of energy materials, but construction of these pipelines commonly causes major disturbance to ecosystems. Due to variability in pipeline installation practices and environments, drawing consensus about how pipeline installations typically impact agricultural ecosystems has been challenging. Here, we conducted a systematic literature review and quantitative analysis of current pipeline studies to determine the magnitude of soil and vegetative responses to pipeline installation and found detrimental impacts to both soil and vegetation variables, including compaction, aggregate stability, and plant biomass. However, best management practices and remediation timeframes vary between studies. Thus, the objective of this study was to determine impacts of pipeline installation on Ohio soil and crop characteristics after a 4- to 5-year remediation period across three independent pipeline installations: the Rover, Utopia, and Nexus pipelines. We performed a 2-year on-farm study in 2020 and 2021 over 29 sites in 8 Ohio counties, directly comparing right-of-way (ROW) and adjacent, unaffected areas (ADJ) of the same agricultural fields. Soil physical, chemical, and biological properties were evaluated, as well as yield and stand counts for field corn, corn silage, and soybean. Detrimental impacts to soil physical characteristics which occurred during pipeline installation persisted through this study period, while variable impacts to soil chemical properties were observed on an individual iii site basis. Finally, satellite image-derived normalized difference vegetation index (NDVI) was used to analyze if ROW versus ADJ differences in agricultural crop yields can be evaluated in a less time- and labor-intensive process compared with traditional on-farm sampling methods. Various soil and yield metrics show that degradation of agricultural land persists past the 4- to 5-year rem (open full item for complete abstract)

Committee: Steve Culman (Advisor); Scott Demyan (Committee Member); Sami Khanal (Committee Member) Subjects: Agronomy; Energy; Environmental Science; Soil Sciences