Symposium Proceedings

 

Note: Presentations are grouped by the student’s area of research (based on the faculty mentor’s academic department), not the student’s academic major.

 

Poster Session E: 

1:30 - 2:30 pm

Chemical Engineering; Chemistry; Civil and Environmental Engineering; Electrical and Computer Engineering; Engineering Technology; Geology; Industrial Engineering and Management; Mathematics; and Statistics (45 posters)

 

Presentations:

 

E-01     Tylee Kareck

Research Collaborators:  Paritosh Ramanan, Zheyu Jiang, Saba Ghasemi Naraghi, Ricky Reed

Research Presentation Title:  Microgrid Optimization: Hydrogen Technology Modeling

Faculty Research Mentor:  Zheyu Jiang, Chemical Engineering

 

The U.S. chemical manufacturing and refining industries are two of the largest sources of energy demand and greenhouse gas (GHG) emissions in the country. They account for 15% of the country’s energy consumption and nearly 20% of the U.S.’s greenhouse gas (GHG) emissions. Process heating creates most of these energy requirements and GHG emissions. Process heating is typically generated through direct fossil fuel combustion or steam, which also consumes fossil fuels. As the country moves toward carbon-neutrality and decarbonized electricity, chemical industries are seeking paths toward decarbonizing process heating. One pathway currently being considered is electrification. To truly reduce the industry’s carbon footprint, it is necessary to integrate chemical plants with decarbonized energy systems and reduce emissions within the energy grid. However, integration efforts are currently challenged due to hesitance in directly sharing process data with Independent System Operators (ISOs) due to the private and sensitive nature of such data. In order to enable integration between electrified process heating systems and the power grid without direct data sharing, the present project develops decentralized algorithms for chemical plants and ISOs to use in operations planning while accommodating data privacy. Development began by establishing key chemical process heating applications with a high potential for electrification. One such process is steam cracking. Steam cracking is a highly endothermic petrochemical process that converts saturated hydrocarbons into smaller unsaturated hydrocarbons, such as converting natural gas into ethylene and propylene. This requires substantial process heating, but various electrification methods are possible, such as using hydrogen. The present study examines the plant-level microgrid for this process and formulates operational constraints related to its components for an optimization model. This presentation focuses on mathematically modeling proton-exchange membrane (PEM) electrolysers and fuel cells, two important operations within the microgrid. Various models and simulations of these operations were compiled from literature and used in creating constraints. Constraint formulation for other hydrogen technologies and infrastructure is also discussed. Future developments in this project are expected to include a larger, more integrated model and exploration into various pricing effects. 

 

E-02     Kaitlyn Luster

Research Collaborators:  Razaul Karim

Research Presentation Title:  Spent Coffee Grounds - Derived Carbon Adsorbents for Carbon Dioxide Capture

Faculty Research Mentor:  Hong Je Cho, Chemical Engineering

 

CO2 emissions are the primary driver of global warming, climate change and ocean acidification, which mainly occur from the processing of various consumer goods and fossil fuels. Reducing these emissions has become one of the major challenges. To address these challenges, we aim to develop low-cost carbon adsorbents effective for CO2 capture, utilizing readily available biomass waste in the form of spent coffee grounds (SCG), via pyrolysis with metal activating agents. In this symposium, we will discuss two major effects on the carbon’s CO2 adsorption abilities: 1) the types and amounts of activating agents (e.g., MgCl2, FeCl3, CaCl2, and KOH), and 2) the mixing methods (i.e., dry or wet) for SCG-activating agent mixture, prior to pyrolysis. The obtained results will not only make significant strides in advancing sustainability through the utilization of biomass waste as carbon precursors, but also play a crucial role in mitigating the adverse effects of climate change. The knowledge and insights acquired from this project will provide solid groundwork for further investigations into the impacts of carbon’s porous structures on carbon’s abilities to adsorb CO2. 

 

E-03     Sean Smart

Research Collaborators:  Hong Je Cho

Research Presentation Title:  Nitrate Removal Using Carbon Adsorbents Derived from Spent Coffee Grounds

Faculty Research Mentor:  Hong Je Cho, Chemical Engineering

 

Nitrates in water are an increasing problem in rural areas. Nitrates get into water from fertilizers applied at farms or residential areas, that then get washed out into drainage. The nitrates then get into rivers and groundwater. Rural areas are especially likely to have nitrates in their drinking water due to filters for nitrates usually being large and expensive, two factors that discourage rural people from being able to filter nitrates. Our research is therefore focused on eliminating nitrates from the water using spent coffee grounds (SCG) as a source of carbon to produce a nitrate filter.

In this study, we want to demonstrate that SCG-derived carbon can effectively remove nitrates from water via adsorption. SCG-derived carbon was prepared by the pyrolysis of SCG with metal activating agents of FeCl3. We found that the carbon preparation methods significantly affect the resultant carbon’s nitrate removal abilities, such as the amount of FeCl3, the impregnation methods of SCG and FeCl3 (i.e., dry, wet or incipient wetness mixing) prior to pyrolysis, and the pyrolysis temperature and time. The best carbon sample was obtained from the conditions of 40wt% FeCl3, incipient wetness impregnation and pyrolysis at 600 °C for 1.5 hr, exhibiting 15 mg nitrate removal per g-carbon. The knowledge and insights gained from this project will lay the foundation for future studies, such as the impact of types of metal activating agents on nitrate removal performances of SCG-derived carbon.

 

E-04     Griffyn Stoodley

Research Collaborators:  Berk Uysal, Bhuvana Plakkot , Madhan Subramanian, Sundar Madihally 

Research Presentation Title:  Effects of Galvanotaxis on 3D Bioprinted Astrocytes

Faculty Research Mentor:  Sundar Madihally, Chemical Engineering

 

Adapting 3D printing to create custom devices and medications has seen significant interest in biomedical and pharmaceutical sciences.  Many are exploring the usage of 3D printing to develop cell-laden structures for use in drug screening and 3D cell culture development.  However, the effect on cells of bioprinting and bioinks is not well understood.  Previously our group observed elongation of cells after printing through a 34G nozzle. The functional effects of such changes to the cell are not well understood.  In this regard, this project looked to evaluate the effect of printing and electrical stimulus.  The movement of cells due to electrical stimulus, known as galvanotaxis, is a phenomenon observed in many cell types including neurons, and adult stem cells.  Previously our group engineered a compact galvanotaxis device that is easily adaptable to in vitro cultures.  The purpose of this study was to understand the role that galvanotaxis plays in the potential morphological changes of elongated 3D bioprinted human astrocytes.  These cells are involved in adaptive immune responses in the central nervous system. A galvanotaxis device with three wells was used. To accommodate this device for 3D-printing conditions, various initial experiments were conducted. Phosphate buffer agarose gel was poured into the outside wells of the galvanotaxis device allowing the center well to be filled with Pluronic (F127). The Pluronic was replaced with astrocyte media after initial formation of the printed hydrogel. An electrical field was applied for 1 hr at 350V and 3mA. Changes in hydrogel (0.75% chitosan and 0.03% gelatin) properties, astrocyte media, and phosphate buffered saline (0.5% agarose) were tested.  These results show stability of materials i.e., no resistive heating and associated denaturing.  The procedure was extended to include 3D printing of astrocytes.  Cells were pre-stained with a non-toxic marker, mixed with hydrogel, and printed.  Cells were exposed to the electrical field for 1hr and cultured for five days. Results show some cells alignment with the electrical field and potential of using 3D printing for developing cell-containing devices. 

 

E-05     Holly Anthony

Research Collaborators:  Colton Calvert

Research Presentation Title:  Light-Driven Processing of Biomass Burning Organic Aerosol from Eastern Red Cedar

Faculty Research Mentor:  Elijah Schnitzler, Chemistry

 

Biomass burning is an important source of light-absorbing organic aerosol, or brown carbon, in the atmosphere. Brown carbon impacts climate directly by absorbing and scattering light. These nanoparticles can stay suspended in the atmosphere for two weeks in the troposphere, and during this time they can undergo light- and oxidant-driven chemical processing, which in turn influences their climate effects. Here, we investigate the light driven processing of brown carbon samples generated in-house using a tube furnace and collected onto quartz fiber filters. The filters were extracted in water, dried, subsequently extracted in methanol, diluted to give different mass concentrations of water-soluble and -insoluble species, and then placed into a photoreactor to mimic the process of aging in the atmosphere. The samples were in the photoreactor for eight hours total but taken out in one-hour intervals to be analyzed with a UV-vis spectrometer. The samples of brown carbon exhibited an initial absorption enhancement followed by uniform whitening. Effects of initial mass concentration were also explored to probe the mechanism of light-driven processing. These observations help constrain the fate and impact of brown carbon aerosol in the atmosphere.

 

E-06     Kaitlin Ashcraft

Research Collaborators:  Mayokun Ayodele

Research Presentation Title:  Intermittent Illumination using Modern LED Technologies to Study Radical Chain Reactions

Faculty Research Mentor:  Spencer Pitre, Chemistry

 

The main goal of this research study is to discredit the use of light on/off experiments to consider if the overall mechanism of photoredox reactions involves radical chain propagation. The common misconception is that in a light on/off experiment, if no conversion is observed during the light off period, there is no chain propagation involved in the mechanism. However, this method does not provide any insight into the reaction mechanism, as chain reactions are usually terminated within milliseconds to seconds after the light source has been turned off. The usual method often uses minute timescales that are too slow to provide any insight into chain reactions since these occur in shorter timescales. Our new method uses an updated “rotating sector method” that leverages modern LED technologies to demonstrate how intermittent light on a shorter timescale of microseconds to seconds can show if a chain reaction occurs and can be used to calculate the average lifetime of the propagating chain. In this presentation, we will discuss the implementation of our updated intermittent illumination method to study radical chain reactions occurring in the Minisci alkylation of heteroarenes and the dehalogenation of vicinal-dibromides.   

 

E-07     Jace Barton

Research Collaborators:  Elijah Schnitzler, Micah Miles

Research Presentation Title:  Effect of Ozone on the Light Absorption of Nanoplastics in the Atmosphere

Faculty Research Mentor:  Elijah Schnitzler, Chemistry

 

Plastic particles with diameters below a micrometer, or nanoplastics, are an emerging contaminant in the atmosphere. These nanoplastics are small enough to stay suspended in the troposphere for up to two weeks, during which they can impact climate directly by scattering/absorbing sunlight; however, the effects of atmospheric oxidants on the absorptivity that dictates this effect are not well known. Here, we investigate the effects of ozone, a ubiquitous oxidant in the atmosphere, on the light absorption of nanoplastics. Nanoplastic samples were generated from filaments passed through the heated nozzle of a 3D printer, collected on glass-fiber filters, and then exposed to ozone in a flow-tube reactor. Several representative plastic materials and colors were used to generate the particles. The light absorption of the filter-collected nanoplastics was measuring using UV-vis spectroscopy. The time dependence of color in the presence of ozone will be presented and discussed in the context of atmospherically relevant exposure times. Comparisons will also be drawn to light-driven processing, in contrast to oxidant-driven processing, to determine the relative importance of these processes in governing the direct effect of nanoplastics on climate. 

 

E-08     Roman Bersche

Research Collaborators:  Gabriel Cook

Research Presentation Title:  The Preparation of Nanodiscs with Varying Components and the Incorporation of Membrane Proteins

Faculty Research Mentor:  Gabriel Cook, Chemistry

 

Nanodiscs provide a biologically relevant mimic of lipid environments for studying membrane proteins outside of the cell membrane. Nanodiscs, which are comprised of lipids and an amphipathic membrane scaffolding protein (MSP), self-assemble into bilayer discs that behave like a patch of cell membrane. By incorporating membrane proteins into these environments, biophysical properties of these proteins and their interactions can be characterized at the molecular level. The composition of biological membranes are complex and creating nanodiscs with multiple lipids and varying mixtures can lead to a more accurate mimic. The various forms of nanodiscs explored here include mixtures of uncharged and charged phospholipids, mixtures of cholesterol and phospholipids, and mixtures of proteins and phospholipids. The preparation of various nanodiscs may be accomplished using diverse pathways, such as utilizing biobeads, b-cyclodextrin, or dialysis to remove residual detergent, probing the possibility of greater efficiency in nanodisc formation. This study evaluates the different strategies for making protein-containing nanodiscs. These studies provide a building block for creating more sophisticated mimics and a more accurate way of studying interactions of disease causing proteins within biological membranes. 

 

E-09     Sara Coffey

Research Collaborators:  Shubham Sharma

Research Presentation Title:  Optimization of Iron Pyrite Nanoparticles

Faculty Research Mentor:  Yolanda Vasquez, Chemistry

 

Non-noble metals can be utilized in heterogeneous catalysis, which plays a crucial role in converting natural resources into a wide array of valuable products spanning fertilizers, chemical fuels, commodity chemicals, polymers, and pharmaceuticals. Additionally, it holds significant promise for enhancing energy conversion and storage, alongside aiding environmental remediation. The precise regulation and adjustment of catalyst shape and size are fundamental for advancing energy-efficient and environmentally friendly catalytic processes. In alignment with this objective, our current research focuses on the wet-chemical synthesis of shape- and size-tunable iron pyrite nanoparticles (FeS2) using iron oxy-hydroxide (β-FeOOH) nanoparticles. This project aims to optimize the parameters of time, temperature, and concentration for both the iron precursor and sulfur source, to achieve a selective size range of 150 to 200nm FeS2 nanoparticles. This tailored size optimization is critical for improving the selectivity and yield for the selective reduction of nitroarene compounds to the desired imine (C=N) formation. 

 

E-10     Georgia Eastham, Adonis Gardner

Research Presentation Title:  Probing the dynamic behavior of cyclohexane using classical models

Faculty Research Mentor:  Martin McCullagh, Chemistry

 

Cyclohexane is a textbook model used to discuss the concepts of molecular strain and conformational interconversion in undergraduate organic chemistry courses. The rate of interconversion and/or relative population of conformers can be impacted by temperature, solvent environment, and chemical substitutions on the cyclohexane ring. In this work, we investigate the ability of classical models to capture this behavior.  Additionally, we use quantum chemical calculations to help parameterize components of the classical force field and quantify the roles of these components on determining the rates and relative populations.  These insights deepen our understanding of cyclohexane's behavior in diverse chemical environments, offering new information about a textbook example. 

 

E-11     Noah Holt

Research Presentation Title:  Exploring the Properties of CO2 Adsorbing Materials

Faculty Research Mentor:   Nicholas F. Materer, Chemistry

A combination of experimental and computational methods provide insight into the interactions between poly-amine based materials and CO2.   

 

E-12     Hadley Keith

Research Collaborators:  Tim Schoch

Research Presentation Title:  Investigation of the Benzyl Esterification of trans-Arylcycloalkenes

Faculty Research Mentor:  Jimmie Weaver, Chemistry

 

Medium ring -arylcycloalkenes (ACs) are a synthetically useful, yet insufficiently understood motif in organic chemistry. The focus of this research was to characterize a rational series of trans-1-ACs through accurate determination of their reaction rates with benzoic acid to the corresponding benzoate esters. Toward this, cis-1-ACs were prepared by Grignard addition—Dean Stark elimination sequences to undergo subsequent photoisomerization to their trans-isomers. This was accomplished quantitatively by sensitized irradiation in a blue LED photoreactor under controlled conditions. The two essential modular structural components of 1-ACs (arene and cycloalkene) were probed. Nuclear magnetic resonance spectra (NMR) were obtained of each 1-AC at various time points and their conversion analyzed. 1-ACs with excessive steric hindrance on the cycloalkene ring showed decreased reactivity. Interestingly, phenylcycloheptene formed an unidentified product within the first 10 minutes of irradiation, and by 2 hours, complete dimerization was observed. Regarding the aromatic ring, electron-donating substituents accelerated the esterification reaction while electron-withdrawing groups stopped it entirely. 

 

E-13     Katelyn Laminack

Research Collaborators:  John Hayford, G. Teye-Kau, Spencer Pitre

Research Presentation Title:  Vitamin B_12 Photocatalyzed Cyclopropanations Using Bromoform as a Methylene Source

Faculty Research Mentor:  Spencer Pitre, Chemistry

 

Cyclopropyl groups are of great importance in medicinal chemistry and are extensively exploited in the development of new pharmaceuticals. Adding a cyclopropane ring can influence the intrinsic lipophilicity, metabolic stability, binding to target proteins, and alter the pKa of a potential drug candidate. Cyclopropanes are also invaluable building blocks in organic synthesis owing to their unique structural and electronic properties. Therefore, due to their importance in both medicinal and synthetic chemistry, having reliable and efficient methods for the preparation of cyclopropanes would be of great value to the chemical community. In previous work, our lab has shown that Vitamin B12 can effectively photocatalyze the cyclopropantion of electron deficient alkenes using dichloromethane, a common and inexpensive organic solvent, as the methylene source. Our lab is interested in expanding this chemistry to other 1,1-dihalo precursors to efficiently prepare substituted cyclopropanes in a single step. In this work, we present our initial investigations into the preparation of monobromo-substituted cyclopropanes photocatalyzed by Vitamin B12 using bromoform as a methylene source. Our reaction optimization and progress on the reaction scope will be presented.  

 

E-14     McKenzie Menefee

Research Collaborators:  Cody Godfrey

Research Presentation Title:  Selective N-Alkylation of 1,2,4-triaColes and imidazole

Faculty Research Mentor:  Jeanne L. Bolliger, Chemistry

 

Imidazoles and 1,2,4-triazoles are among the privileged structures which are part of many active pharmaceutical ingredients and agrochemicals. Approved drugs containing the 1,2,4-triazole unit include the antifungal agent fluconazole and the chemotherapeutic letrozole. Imidazole units are found in the antifungal drug miconazole, fexinidazole (used to treat sleeping sickness), and the agrichemical fungicide prochloraz.

In this presentation we will show the selective N-alkylation of imidazoles and 1,2,4-triazoles in the presence of other nucleophilic atoms. This reaction proceeds with excellent yields and is tolerant to the presence of water and air

 

E-15     Micah Miles

Research Collaborators:  Elijah Schnitzler, Katrina Betz, Christian Escritt

Research Presentation Title:  Aerosolized Black Carbon: Generation, Standardization, and Restructuring of Soot Nanoparticles

Faculty Research Mentor:  Elijah Schnitzler, Chemistry

 

Combustion emissions, whether from biomass burning or diesel engines, include nano-scale aggregates of elemental carbon or soot, often called black carbon. Black carbon influences climate directly, through the absorption and scattering of solar and terrestrial radiation, and indirectly, through the alteration of cloud droplet formation and properties. These effects depend on the structure of the aggregates, which can change during their atmospheric residence time. Here, we investigate the restructuring of soot aggregates upon coating with organic compounds co-emitted by biomass burning, simulating possible interactions between these species in the environment. Fractal nanoparticles were generated using an inverted diffusion burner and then measured using a differential mobility analyzer. The resulting aggregates were exposed to filter-collected organic compounds from biomass burning in a glass bubbler heated in a sand bath. Downstream, where the temperature was lower, supersaturation occurred, followed by partitioning of these species onto the soot aggregates. The size of the aggregates with and without the coating was monitored as a function of the temperature of the coating apparatus. These results show that the inverted flame burner produced high concentrations of soot nanoparticles with a reproducible, standardized size distribution and that coating with organic compounds from biomass burning leads to substantial restructuring of the black carbon cores.

 

E-16     Branson Morgan

Research Collaborators:  Shubham Sharma

Research Presentation Title:  The Optimization of the Hydrogenation of Nitroarenes with Oxy-Hydroxide

Faculty Research Mentor:  Yolanda Vasquez, Chemistry

 

The synthesis of amines and anilines can be expensive with the high cost of necessary noble metal catalysts such as palladium, platinum, gold, and ruthenium. To bypass these expensive and nonrecoverable metal catalysts for the hydrogenation of nitroarenes, we’ve learned that utilizing iron pyrite nanocrystals as a precursor produces a high yield of anilines because of their efficiency in the transfer of hydrogenation in nitroarenes. Though the yield of this synthesis involving the iron pyrite is efficient with yield, we’re taking the precursor to iron pyrite nanocrystals, a compound called oxy-hydroxide (β-FeOOH), into consideration for a further optimized production of anilines. Optimizing the synthesis by utilizing oxy-hydroxide could provide an economic bypass to producing anilines. Our optimization begins with the testing of different increments of oxy-hydroxide to determine which has the highest yield of anilines. The highest yield will provide further insight into the better optimization of the reaction. By further optimizing this reaction, we not only make the synthesis of anilines more reproducible but also more economically viable. 

 

E-17     Abigail Norris

Research Presentation Title:  Mechanistic Study in New Synthetic Methods for N-Alkenyl-Substituted 1,2,4-TriaColones

Faculty Research Mentor:  Jeanne Bolliger, Chemistry

 

The 1,2,4-triazolone unit is found in biologically active molecules that have been used in studies to treat liver-fat buildup as well as hypertension. We will show in this presentation a synthetic method for the preparation and substitution of this scaffold. 

 

E-18     Kaitlyn O'Brien

Research Collaborators:  Cody Godfrey

Research Presentation Title:  Alkoxy substituent variation of ethyl 4-((4–methoxybenzyl)thio)-3-(4H-1,2,4-triaCol-4-yl)benzoic acid

Faculty Research Mentor:  Jeanne Bolliger, Chemistry

 

It is known that many azoles, polyenes, and allylamines have antifungal properties. The purpose of this research is to chemically modify one of our lead compounds which contains an azole, more specifically a triazole unit, in hopes of forming a more effective antifungal agent to target the opportunistic pathogenic yeast, Candida Albicans. Since our lead compound had an ester functionality, we decided to explore the effect of the alkoxy substituents on the antifungal activity. For this we prepared a common carboxylic acid precursor which then was converted in two steps to a range of ester analogues.

 

E-19     Jennie Russell

Research Collaborators:  Pratikshya Paudel, Patrick Combs, Smita Mohanty

Research Presentation Title:  Pheromone Binding to Pest Control: Investigating Olfaction Mechanisms in Ostrinia furnacalis

Faculty Research Mentor:  Smita Mohanty, Chemistry

 

Understanding the molecular intricacies of pheromone binding and release in insects is paramount for developing innovative and eco-friendly pest control strategies. Pheromones are hydrophobic and volatile chemicals that are secreted by female insects to attract the male insects for mating. Pheromone-binding proteins (PBPs) in the antennae of male insects serve a crucial role in transporting hydrophobic pheromone molecules to olfactory receptor neurons (ORN). This process enables male insects to locate a mate. Unraveling this mechanism opens the door to designing synthetic ligands that can compete with natural pheromones, confusing male pests and impeding their mating. Such an approach offers an effective pest mitigation strategy without the reliance on traditional pesticides. The invasive agricultural pest, Ostrinia furnacalis, inflicts substantial damage to crops globally. The highly sensitive olfactory system in male O. furnacalis moths depends on pheromone detection facilitated by PBP. However, the intricate details of pheromone recognition, binding, and release by O. furnacalis PBP2 (OfurPBP2) remain largely unexplored. The current study focuses on the production of recombinant OfurPBP2 and its mutants through bacterial expression, laying the groundwork for future in-depth mechanistic analyses.

 

E-20     Kelby Schrader

Research Collaborators:  Cia ul Quasim Syed, Sathya Samaraweera

Research Presentation Title:  Non-Invasive Control of Diabetes Through Visual Colorimetry

Faculty Research Mentor:  Sadagopan Krishnan, Chemistry

 

Managing diabetes is vital to prevent future problems concerning the vascular, neurological, and visual systems. Individuals with pre-diabetes are required to keep precise glycemic control to maintain a healthy lifestyle, since they face an elevated risk of developing resistance to glucose tolerance and insulin activity. In recent years, popularity has increased in the cheaper and non-invasive diagnostic biosensors that have become available. Our laboratory has been consistently researching insulin immunosensors, with shorter assay times when compared to traditional biological assays.  We focus on achieving high analytical sensitivity in addition to biological sensitivity, high reproducibility (within ±5-10% STDEV among replicates), and leveraging ultra-low detection capabilities facilitated by suitable surface designs (e.g. picomolar and lower). Our recent focus involves a sandwich immunoassay that uses magnetic particles and a horseradish-labeled peroxidase antibody that translates signals into a visual colorimetry system, resulting in an insulin sensor. This approach eliminates the requirement of recurring needle pricking, as this insulin detection is accomplished through visual analysis. The insulin concentration within the sample directly correlates with the intensity of the resulting color. This presentation will consider the sensor’s capabilities, including long-term storage on the sensor’s performance, within various biofluids. 

 

E-21     Joshua Schut

Research Collaborators:  Cia Syed, Saytha Samaraweera, Josh Ramsey

Research Presentation Title:  Development of Multiplex Sensors based on Bioconjugation and Colorimetry

Faculty Research Mentor:  Gopan Krishnan, Chemistry

 

One method of developing multiplex sensors is the use of bioconjugated RNA sequences designated to capture the target sequence. Bioconjugation is the process of bonding a life-essential group, such as RNA or a protein, to a reactive chemical group created on a surface (e.g., nanoparticles or a metal surface as desired). The process of bio-conjugation is known for the deeper study of RNA and proteins because the functional group, the metal, is designed to improve the analysis of the desired target molecules. Our multiplex scanner emphasizes the use of magnetic nanoparticles bioconjugated to RNA sequences like those seen in SARS-CoV-2 strains. A color-producing enzyme is added to the reaction to form color to measure a positive response and the color intensity to indicate an increased presence of the RNA. My lab has spent the last school year developing the method and testing it in different sample matrices.

The process starts by adding carbodiimide to activate -COOH-functionalized magnetic nanoparticles in a buffer suspension. After incubating, the nanoparticles were washed and magnetically separated to bioconjugate a capture RNA sequence-amine end group to form amide bond conjugation with the -COOH-activated nanoparticles. After incubating, the solution was washed and separated with a primer added to prepare a selective capturing site for the target RNA sequence. After a wash and magnetic separation, the target RNA sequence was added to a synthetic saliva solution to simulate real circumstances. A blocker is added to the solution to allow for the binding of the light-sensitive substrate, which is the peroxidase-tagged second complementary sequence to the target RNA sequence (a double and sandwich-type hybridization assembly). After a final wash and separation, the color-generating substrate is added and mixed for 30 seconds. The solution is separated, and the solution will color to show the presence of the target or stay clear to indicate the lack of the target RNA in the sample solution, thus offering an equipment-free point-of-need visual colorimetric sensor for virus RNA detection.

 

E-22     Colton Scott

Research Collaborators:  Cia Syed, Doris Benbrook

Research Presentation Title:  Electrochemical Assay Validation of Cancer Biomarkers for Clinical Studies

Faculty Research Mentor:  Sadagopan Krishnan, Chemistry

 

This presentation will discuss pyrenyl-nanocarbon-based electrochemical immunosensor measuring cancer protein concentrations in clinical serum solutions. Ovarian cancer has the highest mortality rate in female reproductive cancers, namely because of the late stage of detection of the disease and the resistance it acquires to chemotherapy despite 60-70% of patients exhibiting a high response rate. To this end, it is paramount that detailed, analytical, and clinical assays translate to clinical cancer treatment, control, and prevention. The team conducting this research is multidisciplinary in nature that are focused on electrochemical biosensor development to translate to clinically significant cancer biomarkers that can be applied to biofluids. The advantages to an electrochemical approach in biomarkers include shorter assay time compared to biological assays, high analytical sensitivity along with biological indifference, high reproducibility, ultra-low detection capabilities, small sample and reagent volumes, including an option to be partially automated, label and label-free options, and direct biofluid analysis. This culminates to bring a minimally to noninvasive analysis of a patient for ovarian cancer and for clinical assay needs.   

 

E-23     Moriah Thompson

Research Collaborators:  Tiwalola Ogunleye

Research Presentation Title:  Preparation of Recombinantly Expressed T-cell Receptor Protein α (TCRα) for Structural Studies

Faculty Research Mentor:  Gabriel Cook, Chemistry

 

T-Cell Receptor Protein (TCR), a single-pass transmembrane protein found in T-cells, is involved in the signaling pathway in immune response.  TCR binds antigens, activating the T-cell through signal transduction.  The two chains of the receptor, alpha and beta, connect through a disulfide bond.  While this is an essential protein for the immune system, the function and structure of TCR is not fully understood because the hydrophobic transmembrane region makes it difficult to study in standard sample conditions.  Hydrophobic proteins, like this receptor, must be incorporated into detergent or lipid environments to run experiments that are commonly used to determine their function and structure.  Our lab is developing methods to incorporate this hydrophobic protein into samples so that we can use Electron Paramagnetic Resonance (EPR) Spectroscopy and Nuclear Magnetic Resonance (NMR) Spectroscopy to study these properties.  For this work, we are concentrating on expressing and purifying the human alpha chain (TCRα) protein from E. coli.  To run EPR on TCRα, a paramagnetic label must bonded to the protein.  The TCRα protein was mutated at four positions, in four separate sequences, to replace a wild-type amino acid with a Cysteine residue.  These Cysteines will form a thiol linkage with a nitroxide group that will provide the paramagnetic label.  This presentation will explain the methods used to express, purify and concentrate mutations of Alanine 18 to Cysteine (A18C) and Lysine 14 to Cysteine (L14C), for the preparation of samples that can be measured by EPR and NMR. 

 

E-24     Gavin White

Research Collaborators:  Haoran Chong, Barry Lavine

Research Presentation Title:  Every Contact Leaves a Trace

Faculty Research Mentor:  Barry Lavine, Chemistry

 

When two objects come into contact, there is a transfer of material (Locard’s exchange principle) that can be used to associate an individual with an object (e.g., an automotive vehicle) and/or a location (crime scene).  The material transferred is often small and is referred to as trace evidence.  While trace evidence usually cannot individualize a suspect, it is valuable because it can provide linkages and supply information critical to the reconstruction of events that occurred at the crime scene.  For example, a vehicle related fatality such as a hit-and-run where a vehicle hits a pedestrian and then leaves the crime scene.  The only linkage between the vehicle and the pedestrian is from the automotive paint transferred to the clothing of the victim.  In these situations, the layer structure, color, and composition of the automotive paint recovered from the clothing of the victim is characterized and can link or exclude possible vehicles/makes/models/years from association with the crime scene.  Using this information, the forensic paint examiner may be able to develop a suspect which would then allow the paint sample recovered from the crime scene to be compared with paint from the suspect’s vehicle.  This presentation will focus on forensic automotive paint analysis, the techniques currently used in the United States to characterize automotive paint and on-going research at OSU to improve both the speed and accuracy of forensic automotive paint analysis through the application of modern analytical chemistry which is the focus of this poster presentation.    

 

E-25     Dulce Gallardo Owens

Research Collaborators:  Andrea Arredondo-Navarro, Justin Scott, Eliane El Hayek, Jose Cerrato, Jorge Gonzalez-Estrella

Research Presentation Title:  Understanding Rates of Microplastic Generation from Thermally Oxidized Plastics Reactivity in Aqueous Media

Faculty Research Mentor:  Jorge Gonzalez-Estrella , Civil and Environmental Engineering

 

This study assesses the release of derivatives and additives from thermally oxidized plastics into aqueous media. Our group has found that open-pit waste burning generates microplastics (MPs) with signs of thermal oxidation in their functional chemistry. A more oxidized functional chemistry may increase the release of plastic derivates and additives in aqueous media. So far, leaching studies have focused on UV oxidation or low temperature burning. Our group’s preliminary experiments using PVC-MPs have shown that thermally oxidized plastics release more organic derivatives than their non-burned counterpart. In this study, we have selected to work with commercial Styrofoam (expanded polystyrene, EPS) due to its common abundance in water bodies and its demonstrated toxicity to living organisms attributed to its derivatives. Our current work is focused on producing laboratory-made PS-MPs from both thermally oxidized and non-oxidized PS within a specific size range (117-140 µm). Additionally, we are analyzing changes in functional chemistry and morphology of both types of MPs with Attenuated Total Reflectance - Fourier Transform Infrared (ATR- FTIR) spectroscopy and Scanning Electron Microscopy (SEM). Future work will be focused on quantifying the release of Dissolved Organic Carbon (DOC) after reacting the MPs to deionized water and freshwater (1000mg/L) for 168 h. We will also analyze the release of phthalate, Dibutyl phthalate (DBP), and metals using Gas chromatography Mass Spectroscopy (GC/MS), and Inductive Coupled Plasma – Optical Emission Spectroscopy (ICP-OES). Our study will provide relevant results regarding the reactivity of thermally oxidized MPs on environmentally relevant aqueous media.   

 

E-26     Shelby Maggard

Research Collaborators:  Lizzie Long, Mary Foltz

Research Presentation Title:  Optimizing Agriculture: A Modeling Approach to Estimating N2O Emissions from the OSU TAPS Program

Faculty Research Mentor:  Mary Foltz, Civil and Environmental Engineering

 

Nitrous oxide (N2O), a potent greenhouse gas, can be produced through the microbially mediated processes of denitrification and nitrification. Nitrogen-based fertilizers used in agriculture have increased crop productivity, but excess N can stimulate the nitrification and denitrification processes. Agriculture is thus a significant contributor to global N2O emissions. The Testing Ag Performance Solutions (TAPS) program in Oklahoma is a farm management style competition that lets participants trial variations in irrigation and fertilization with the current goal of improving input use efficiency. The Denitrification-Decomposition (DNDC) model can be used to estimate the environmental impacts from differing rates of irrigation and fertilizer application. As such, the objective of this work is to apply DNDC to estimate N2O emissions from the TAPS program in an effort to quantify environmental impacts associated with participant management decisions. Participant fields from the 2020 and 2021 competitions were modeled, evaluated, and further calibrated using averaged measured crop yields. We find the model generally improved yield predictions and predicted lower N2O emissions after calibration. Future research will include field measurements of N2O to better evaluate DNDC and the development of a simplified tool for participants to estimate the environmental impacts of management decisions.  

 

E-27     Gwen Tipling

Research Collaborators:  Dulce Gallardo-Owens, Tori McGruer, Macy Gustavus, Win Cowger, Jorge Gonzalez-Estrella

Research Presentation Title:  Assessment of the Abundance and Type of Microplastics in Sediments from the Pacific Crest Trail

Faculty Research Mentor:  Jorge Gonzalez Estrella, Civil and Environmental Engineering

 

The Pacific Crest Trail (PCT) is a long-distance hiking trail that spans 2653 miles. The trail starts near the border with Mexico, runs along the Sierra Nevada mountains, passes through the States of California, Oregon, Washington and spans all the way to British Columbia, Canada. The PCT receives hundreds of hikers, and although in general, people that hike the PCT are environmentally mindful, human presence can leave plastic waste in the trail. This waste can break down into microplastics, particles with a size between 5 millimeters and 1 micrometer. Microplastics can accumulate in sediments across the trail with unknown effects on the soil environment. For that purpose, sediment samples that have been collected along the entire length of the trail in collaboration Moore Institute for Plastic Pollution Research. Our current work has been focused on processing the soil samples with elutriation, chemical digestion, and density separation. Our future work will be focused on analyzing the abundance and type of MPs in samples with fluorescence microscopy, Attenuated Total Reflectance - Fourier Transformed Infrared Microscopy (ATR-FTIR), and pyrolysis Gas Chromatography (py-GC-MS).  Our work will help to better understand the abundance of MPs trails associated with hiking activity in the PCT.  

 

E-28     Landren Martin

Research Presentation Title:  New Perspective on a Classical Experiment: Understanding the Effects of Asymmetry on the Double-Slit Experiment

Faculty Research Mentor:  Daqing (Daching) Piao, Electrical and Computer Engineering

 

The double-slit experiment performed by Thomas Young over two-hundred years ago established that light has wavelike properties. Since then, methods derived from double-slit experiment have become fundamental to numerous precision measurements.

Textbook understanding of the double-slit experiment has evolved upon analyzing the wave interference associated with symmetric double-slit. Symmetric double-slit refers to the two slits being identical in terms of their physical dimensions (size and shift from the optical axis) and properties (color) of light passing them. A practical configuration of double-slit will, however, never be exactly symmetric between the two slits. And interpreting the interference patterns associated with asymmetric double-slit by assuming symmetric double-slit may bring in systematic error affecting the precision of measurement that double-slit has to offer. 

The objective of this research is to theoretically understand how and to what extent the slit-asymmetry affects the wave-interference of double-slit. The theoretical analysis is based on implementing slit-asymmetry into the Fresnel-Fraunhofer treatment of light standard to modeling double-slit interference. The Fresnel-Fraunhofer treatment calculates the complex electrical field of light on an observing plan as the superposition of the light filed originating from the two slits. By adjusting the asymmetry of the complex electrical fields originating from the two slits, it is possible to analytically predict the resulted double-slit interference for comparing against existing results of numerical simulations [Piao, 2022]. Two types of slit-asymmetries will be considered: asymmetry of the geometric dimensions and asymmetry of the light properties. Starting with ideal double-slit, the effect of slit-asymmetry will be analyzed type-by-type. 

 

E-29     Jasmine Taplin, Soren Petersen

Research Collaborators:  Ruxue Wei, Weili Chang

Research Presentation Title:  Terahertz Spectroscopy Analysis of Plasmonic Surface Waves Resonating in Metal-Silicon Geometries

Faculty Research Mentor:  Weili Chang, Electrical and Computer Engineering

 

Plasmonic surface waves are a unique form of electromagnetic waves that propagate along metal-dielectric interface with unique applications ranging from biological sensing, deep subwavelength lasing, to plasmonic circuitry. The research conducted over the academic year presents three major topics and their implication for terahertz research: numerical simulation, microelectronic fabrication, and terahertz spectroscopy characterization of surface plasmon crystals. Fabrication onto the silicon substrates of varying thicknesses and diameters has included three different processes: photolithography, metallization, and lift-off. The research performed within the optics field includes improving the adhesion abilities of different metals onto a Silicon substrate and implementing systems to refine the fabrication process such as sputtering and plasma etching systems. Various MATLAB simulations were conducted to replicate an image from an article, showcasing a specific aperture shape and array configuration. This demonstrated the capability to focus surface plasmons. Results show distinct evidence of surface plasmon focusing for different simulation variations. Finally, terahertz spectroscopy was performed to characterize resonant excitation of plasmonic surface waves in metal-silicon geometries. These findings have enhanced current understanding of surface plasmon focusing, metal-silicon plasmonic crystals fabrication, and applications in communication technology as well as terahertz optics. 

 

E-30     Mark Bertucci

Research Collaborators:  Mishra Anubhav

Research Presentation Title:  AI Machine Learning in Additive Manufacturing

Faculty Research Mentor:  Hitesh Vora, Engineering Technology

 

This study delves into the seamless integration of Machine Learning AI to enhance energy and material efficiency in consumer and industrial-grade 3D printing. It specifically emphasizes employing AI algorithms as a pivotal tool for detecting failures during the printing process, thereby curbing energy and material waste. Despite the widespread adoption of 3D printing across various sectors from consumer machines to industrial grade, print failures and defects persist as a notable challenge, resulting in a substantial amount of resource waste. Our research aims to address this issue by harnessing AI-driven solutions, particularly utilizing machine learning algorithms implemented on the Raspberry Pi architecture in conjunction with open-source 3D printers for experimentation and training purposes. Our approach involves constructing tailored data libraries to enable our AI system to scrutinize each layer of the print for defects and ensure dimensional accuracy aligned with the original CAD model. Upon identification of anomalies, the system intervenes, automatically halting the printing process to prevent further loss of energy and materials, enabling timely intervention by personnel to rectify the issue and resume printing. This entails the development and refinement of AI models trained on comprehensive datasets encompassing known failure patterns and print irregularities. These known failure patterns are based on 5 common factors including hot-end temperature, Z offset, and flow rate. These models are subsequently deployed to monitor ongoing print jobs, employing a layer-by-layer analysis approach as is conducive to FDM manufacturing. Through iterative training and refinement, the AI system enhances its proficiency in accurately identifying and preempting potential print failures.

The anticipated outcomes of this research endeavor are twofold: first, a tangible reduction in energy and material loss within the 3D printing processes due to a higher print success rate; second, the assurance of print quality through AI-driven quality assurance mechanisms. By integrating AI technologies, both manufacturers and end-users stand to benefit from minimized print failures, thereby optimizing operational efficiency and conserving valuable resources.

 

E-31     Nicholas Watson

Research Presentation Title:  Multigenerational housing

Faculty Research Mentor:  Rachiel Mosier, Engineering Technology

 

With the increases of inflation and the house market being limited multigenerational housing is a great way to build something for your family. Multigenerational homes are a way to help keep wealth in the family branch as well. With readily available resources the benefit of multigenerational housing follows sharing information and new skills with each other, multiple incomes in one house, more opportunities to invest money, having a support system to aid each other when times are stressful. These things may be beneficial to some but not all. In order to decide if multigenerational housing is what is needed for your life you may closely examine the stressors that come with this type of housing. Are the benefits of multigenerational worth putting your time into?  

 

E-32     Eric Lebar

Research Presentation Title:  Structure of Mona Island Faults from High Resolution Digital Elevation Model

Faculty Research Mentor:  Lao-Davila, Geology

 

Mona Island is a small, uninhabited carbonate platform located in the Caribbean between the islands of Puerto Rico and Hispaniola. It is no stranger to tectonic activity as it is situated in the Mona Rift Valley and just south of the North American-Caribbean plate boundary. Previously there were thought to be faults on the island, but their location differed among researchers. However, with the new lidar (Light Detection and Ranging) technology the island can be studied from a broader perspective. This project focuses on if there is evidence for fault line presence on this island using DEM (Digital Elevation Modeling) and hill shade data on QGIS. Identifying the fault lines on this island and tracking how they formed can help us better understand how faults act in the surrounding ocean as they typically cause more damage through tsunamis than the on-land faults themselves. Faults were tracked by using an elevation profile over a strip of the island; if there is a sudden, unexpected drop then there is evidence of a fault in that region. After data collection there was evidence of a fault cutting through the middle of the island and a scarp was found on the eastern edge of the island as well. 

 

E-33     Jacqueline MacGregor

Research Collaborators:  Brandon Spencer, James Knapp

Research Presentation Title:  Exploring Cambrian Rhyolites: Geochemical and in situ Geochronological Analysis of the Wichita Mountains, Southwest Oklahoma

Faculty Research Mentor:  Brandon Spencer, Geology

 

The Wichita Mountain range in southwestern Oklahoma has traditionally been interpreted to be formed due to a failed continental rift, or aulacogen. However, there have been interpretations that the Wichita Mountains, or more precisely, the Wichita Igneous Province (WIP), are not the result of a failed rift, but formed by alternate processes such as magmatic activity during transform faulting. Several of the magmas in the WIP produced rhyolites; these rocks have been studied from a stratigraphic and geochemical perspective by several workers but are still poorly understood due to several factors. Here, we present preliminary O2 and H2O fugacity and crystallization temperatures estimates of the Carlton Rhyolite group along with compiled geochemical data from the literature in an attempt to characterize intensive properties of early felsic magmas that formed within the WIP. Additionally, we present preliminary in situ zircon U-Pb dates from Carlton Rhyolite thin sections obtained from EPMA analysis.  

 

E-34     Elizabeth Scrudder

Research Collaborators:  Trenity Ford

Research Presentation Title:  The use of Micro-CT in assessing the relationship between oxygen and test volume in the benthic foraminifera Uvigerina peregrina

Faculty Research Mentor:  Ashley Burkett, Geology

 

Variability in the volume of benthic foraminifera tests has been proposed as a potential indicator of changes in the available bottom water oxygen in their environment. Published evidence has been put forward that shows an inverse correlation between test volumes and available oxygen, but there is still significant uncertainty and limited research has been performed to this point. To further clarify the relationship between test volume and bottom water oxygen in infaunal benthic foraminifera, volumetric analysis is being performed on Uvigerina peregrina specimens sampled from different bottom water oxygen environments.  A set of specimen samples has been imaged using micro-computed tomography (Micro-CT).  Micro-CT images have been reconstructed in ORS’s Dragonfly software where scans are converted into three-dimensional models that can be manipulated and refined. Regions of interest (ROIs) were created to highlight specific regions of the specimen to obtain accurate measurements of the volumes of the whole test and the initial chamber called the proloculus. The surface area and diameter of the foraminifera’s test are also computed from the generated model.  A dataset has been created from this process which allows for comparative analysis between ratios of volume, diameter and the measured oxygen levels at the sample location. Using this dataset, the relationship between oxygen availability and both whole test and proloculus volumes will be examined. This has the potential to provide a better understanding of how environmental conditions affect foraminifera chamber growth and enhance our understanding of this as a potential paleoceanographic proxy.

 

E-35     Emily Tompkins

Research Collaborators:  James Knapp, Brandon Spencer

Research Presentation Title:  Mapping Contacts in the Wichita Igneous Province with GIS

Faculty Research Mentor:  James Knapp, Geology

This project is to determine and understand the boundary between the Mt. Scott granite and the gabbro. To help understand this boundary we are using ArcGIS Pro and reading previous research done in this area. To gather more information and new data ArcGIS Pro is used for making maps the contact and making contour maps. Also, interpretation of geologic significance of the surface geometries is done in the Wichita Mountains. Learning more about this contact will help in understanding the formation of the Wichita mountains.   The Wichita Igneous Province (WIP) of southwestern Oklahoma has long been interpreted as an aulacogen, or a failed rift arm formed during the Cambrian. Igneous units in the WIP generally “dip” structurally to the south according to previous workers, but the map expression of the contacts is linear, suggesting steeply dipping contacts which may be fault- or intrusion-generated. This offering presents new contact mapping results based in ArcGIS Pro and confirmed in the field, intended to further delineate the structural and stratigraphic relationships between two significant units in the WIP, the Mount Scott Granite and Mt. Sheridan Gabbro. Pseudo-3D topographic profiles were extracted from the map and analyzed to show potential structural offset and/or intrusive geometries. Preliminary results suggest geometries of some intrusive contacts are inconsistent with their original configuration and have been structurally modified. In some cases, local vertical relief in excess of 100 m may indicate the location of individual fault contacts. 

 

E-36     Kaden Bush, Benny Rohan, Lillia Springer

Research Collaborators:  Pratima Saravanan, Benny Rohan, Lillia Springer

Research Presentation Title:  Effect of Artificial Intelligence on the Cognitive Workload of Students

Faculty Research Mentor:  Pratima Saravanan, Industrial Engineering and Management

 

Artificial intelligence (AI) is being widely lauded for its role in education. Personalized learning, adaptive learning, virtual tutors, and language transitions are increasingly used by students in the recent years. Specifically, Large Language Models (LLM) such as ChatGPT, an AI powered conversational agent is very popular due to its ability to have natural and engaging conversations. Such AI tools are also prone to biases, ethical concerns (privacy), misinformation, and security risks, and has the ability to make their users over-rely on them. Though several studies showed the advantages of LLM on education, little is known about their impact on the cognitive workload of students. To overcome this gap in knowledge, this study aims to investigate the attitude and cognitive workload of engineering undergraduate students to ChatGPT. We plan to seek the following questions through our research: (1) Do students think before using AI on assignments? (2) How much do students rely on AI? (3) Are students thinking outside the box when using AI? (4) What is the effect of AI on the cognitive load of students? To study these research questions, we plan to develop a system that mimics an engineering assignment. This short assignment will ask the participants to write a code, write summary in technical summary, and solve a mathematical problem. The students will be given access to ChatGPT, and their interaction with the AI and the system will be continuously recorded to study their attitude towards AI. We plan to employ eye-tracking to capture their interactions with the AI and study their cognitive workload through gaze pattern and pupil diameter metrics. The findings of this research will help us better understand how AI can impact students and their cognitive workload and develop strategies or interventions for the effective use of AI in the curriculum. 

 

E-37     Grace Hendrix

Research Presentation Title:  Political Districting to Minimize County Splitting and Achieve Minority Representation

Faculty Research Mentor:  Austin Buchanan, Industrial Engineering and Management

 

Every decade, the United States Census Bureau carries out a constitutional mandate to conduct a nationwide census, a cornerstone of our democratic process as outlined in Article I Section 2 of the U.S. Constitution. This pivotal census guides the redrawing of legislative district lines. With this data, states attempt to draw district lines that meet a variety of legal criteria, creating districts that have a small population deviation, relative compactness, and preservation of political subdivisions. Optimization techniques can be applied to analyze some of these criteria individually; however, analyzing multiple criteria simultaneously is a more difficult quantitative endeavor. Prior research indicates the minimum number of county splits necessary to meet population deviation guidelines; however, states commonly have many more county splits. Some suggest that more splits are necessary to abide by other legal criteria, such as the Voting Rights Act of 1965. Is this true? Is it possible to achieve both simultaneously? Using mathematical modeling and optimization techniques, this project seeks to build upon existing research to analyze the tradeoffs between county splits and minority representation in the legislative districting maps of selected states. The states of Arkansas, Illinois, and Wisconsin were selected due to recent court cases and widespread political affiliations across these states. This research seeks to uncover the practical implications of districting decisions, identifying gaps between theoretical requirements and actual maps. Through this analysis, this research endeavors to contribute to a more impartial and equitable approach to districting, aligning with democratic principles of representation. Preliminary results on the compatibility between minimum county splits and minority representation have been promising.  

 

E-38     Connor Meissner, Alexander Leon, Rachel Davis

Research Presentation Title:  Influence of Physical Fatigue on the Cognitive Workload of Individuals

Faculty Research Mentor:  Pratima Saravanan, Industrial Engineering and Management

 

Cognitive workload refers to the mental effort needed for a specific task and is affected by factors like task complexity, information volume, individual expertise, and the task environment. High cognitive workload may result in fatigue, errors, and reduced performance. Measuring cognitive workload is challenging as it depends on several individual factors (e.g., age, demographics, and stress tolerance levels) and environmental factors (e.g., occupation). Several past studies focused only on studying cognitive workload experienced by individuals while performing a mentally demanding task. However, very limited work focuses on the influence of physical fatigue on the cognitive workload of an individual. This is critical since physical fatigue can inherently impact cognitive skills, and increase cognitive workload (e.g., a surgeon performing a complex surgery while standing for several hours). Through this research we aim to investigate the effect of varying levels of physical fatigue on the cognitive workload of individuals. For this research, we plan to recruit college students within the age range of 18-24 years due to ease of accessibility. Participants will be asked to walk on a treadmill to induce physical fatigue, and the cognitive workload will be induced by asking the participants to read-off the screen and solve basic math. Cognitive workload will be measured using eye-tracking technology and physiological measures of participants. Tobii Pro Glasses 3 will be used for tracking participants eye metric, such as blink rate, pupil dilation, gaze, and fixation. Empatica EmbracePlus will be employed for collecting physiological measures, such as heartrate, skin temperature, and electrodermal activity. Subjective mental workload will be assessed using NASA Task Load Index (NASA-TLX). We anticipate that our findings will help us quantify the effects of physical fatigue on the cognitive workload of individuals. This work is important as better understanding of the relationship between physical fatigue and mental performance has profound implications for those employed in physically demanding careers. Our findings can help improve workplaces for these individuals and promote a better quality of life.  

 

E-39     Ethan O'Connor

Research Presentation Title:  Towards Personalized Inhalation Therapy by Correlating Chest CT Imaging and Pulmonary Function Test Features Using Machine Learning

Faculty Research Mentor:  Chenang Liu, Industrial Engineering and Management

 

Inhalation therapy is the predominant method of treatment for a variety of respiratory diseases. The effectiveness of such treatment is dependent on the accuracy of medication delivery. Thus, personalized inhalation therapy wherein inhaler designs are specifically suited to the patient’s needs is highly desirable. Although computational fluid-particle dynamics (CFPD)-based simulation has demonstrated potential in advancing personalized inhalation therapy, it still requires a 3D model of the patient’s respiratory system. Such a model could be constructed with computed tomography (CT) images; however, CT scans are costly and have a high risk of radiation exposure. This concern motivates this study to bridge chest CT images and pulmonary function test (PFT) data, which is noninvasive and easy to obtain. To achieve this goal, an autoencoder is leveraged to find a lower dimensional representation of the CT image; PFT data is then mapped to the encoded image using partial least squares (PLS) regression. Using the decoder in the trained autoencoder, a CT image can be reconstructed by the encoded image predicted by PFT data. This method would allow for greater accessibility to chest CT imaging without exposing patients to the potential negative effects of CT scans, significantly advancing personalized inhalation therapy for respiratory diseases. The results of preliminary experiments using a real-world dataset demonstrate promising performance with our proposed approach. 

 

E-40     Jack Seiler

Research Collaborators:  Prudhvi Raj Pola

Research Presentation Title:  Preliminary Estimation of Mechanical Properties of 3D printed metals

Faculty Research Mentor:  Ranji Vaidyanathan, Materials Science and Engineering

 

Additive manufacturing has become a rapidly emerging technology in many automotive and aerospace industries. Additive manufacturing (3D printing) has made the process of creating and producing complex parts in a three-dimensional way in a layer-by-layer fashion much more accessible than traditional methods. However, while additive manufacturing has benefited many industries, the rapidly developing technology still has drawbacks. One of the most significant drawbacks to additive manufacturing is the time-consuming and costly testing process of the printed parts. To further elaborate, the characterization of additively manufactured parts could take up to 2 years. While additive manufacturing has garnered promising results and benefits for the industries that apply it, the time-consuming characterization process is determinantal when using additively manufactured parts, which must be reduced. In order to counteract this, we use preliminary estimation to evaluate the qualifications of additively manufactured metallic materials. This can be achieved by measuring the stiffness/modulus at various locations of the part in order to estimate the mechanical deformation of the part. This process would use nondestructive techniques such as indentation for hardness and micro tensile testing to predict elastic moduli values at specific locations on the part. Using the values gained from those techniques, they would be put into modeling software to estimate stress distributions or mechanical deformation of the part. Alternatively, the Hall-Petch equation can be used to get the relation between yield strength and the average grain size of a part. This is a probable estimation of the yield strength, allowing the additively printed to be used in accordance with the part’s requirements. Using these approaches can allow the possibility of estimating or predicting some mechanical properties, which can lead to the evaluation of the lifetime of a part. Hence, we can reduce the time required for the qualification of an additively manufactured part to some extent.

 

E-41     Jensen Bridges

Research Collaborators:  Archer

Research Presentation Title:  Statistics on Permutations Avoiding Two Patterns

Faculty Research Mentor:  Melissa Emory, Mathematics

 

In this project, I calculated nine statistics on cyclic permutations in one-line notation that avoid two patterns in its cycle notation, including peaks, inversions, descents and idescents, excedances, and left to right and right to left minimums and maximums. Furthermore, I proposed bijective functions that find all such statistics for each permutation of any given n. 

 

E-42     Taylor Johnson

Research Presentation Title:  Assessing Productivity of Secondary Mathematics’ Discussions and Activities

Faculty Research Mentor:  Michael Tallman, Mathematics

 

Mathematics’ discussions and activities largely shape students’ conceptualizations and dispositions in mathematics. It is crucial for educators, particularly at the secondary level, to facilitate discussions and activities that not only engage students but develop productive reasoning.  The purpose of this research is to create a theoretical framework “assessing productivity” of discussions and activities based on related literature and research. This framework will analyze various aspects such as the students’ independent reasoning and prior knowledge required. The emphasis is to be looking for indicators of how to promote student understanding at a deeper level than memorization or getting correct answers. Then, this framework will be applied to analyze previously recorded data collected by my research mentor of a pre-service mathematics educator’s instruction in a secondary classroom. After the initial teaching videos were recorded, the participant went through a series of interviews where she noted moments of high-quality instruction and room for improvement within her lessons that were recorded. The participant’s personal assessment and reflection of her own teaching will then be compared with the theoretical framework’s assessment of what discussions and activities were productive in the lessons. The hope is that this framework can be applied at a large-scale level when deciding what curriculum should be used in secondary mathematics classrooms or a personal level as teachers plan for their day to day.  

 

E-43     Jesse Wallace

Research Presentation Title:  Controlled Local Isometric Embeddings of Riemannian Surfaces into Euclidean 4-Space

Faculty Research Mentor:  Sean Curry, Mathematics

 

A Riemannian surface tries to characterize abstractly the intrinsic geometry of a two-dimensional surface without reference to three-dimensional space. One would hope that the mathematical description of Riemannian surfaces in the abstract would correspond to our understanding of actual surfaces of physical objects in 3D space. This, however, is a fundamental open problem in Differential Geometry and Partial Differential Equations. The troublesome case is when the intrinsic geometry of a surface looks very close to that of a plane but differs slightly, in which case the partial differential equations degenerates and therefore lies on the boundary of what has been understood. My thesis strengthens a classical result that any Riemannian surface can be realized as a surface in 4D space, by showing that it can be made to lie in certain prescribed three-dimensional subspaces which can be taken to approximate standard Euclidean three-dimensional space. 

 

E-44     Brianna Wolford

Research Collaborators:  Allison Dorko

Research Presentation Title:  Students' Learning from Online Homework

Faculty Research Mentor:  Allison Dorko, Mathematics

 

College students spend more time doing math while they are doing homework than they do during their mathematics class time. However, researchers know little about what students learn from doing homework. Our study employs Piagetian learning theory to investigate what students learned from a series of online homework assignments. Preliminary results indicate that students learned “solve for x” can mean “x= [formula]” or “x= [number],” a modification to their previous knowledge in which “solve for x” always meant “x= [number].” Students also learn to attend to this behavior of a graph when solving inequalities, and how to find the intercepts of linear functions.  

 

E-45     Cenjia Zeng

Research Collaborators:  Lu Zhang, Niranjan Pokhrel

Research Presentation Title:  The Effects of Nitrogen and Epicormic Shoots Damage on Pecan Nut Production

Faculty Research Mentor:  Lan Zhu, Statistics

 

The yield of pecan nuts in Oklahoma will be affected by extreme weather conditions such as hail and tornadoes. This weather will damage the canopy of pecan nut tree thus decrease its production. Since then, it is valuable to study the potential relationship among these factors. This research aims to find the effects of nitrogen treatment and epicormic shoots removal level on yield and nut quality by using data from previous research. The method treats three epicormic shoots removal level (0,50,75) and three nitrogen treatment level (zero, half, full) as independent variables, then apply general linear regression, multinomial logistic regression, post-hoc test, ANOVA test, pairwise t-test, Shapiro test to find out effects on dependent variables: starch, sugar, trace element and nuts quality. The result showed that both nitrogen treatment and epicormic shoots removal effects yield and quality, the right combination can make pecan nut contain more sugar and starch. These results offer valuable insights for pecan nut farmers, enabling the development of improved planting programs and extreme-weather resilience strategies to boost yields and economic returns.