Engineering Undergraduate Research Theses and Honors Research Theses

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Undergraduate Research Theses and Honors Research Theses from the College of Engineering. More about the College of Engineering Honors Program can be found at: https://engineering.osu.edu/honors

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    Microscale Engineering of Blind-Ended Lymphatic Capillaries
    (The Ohio State University, 2024-12) Tinapple, Joseph; Song, Jonathan
    The lymphatic system plays a key role within the body by regulating tissue-fluid homeostasis and coordinating immune responses [1]. This system is comprised of three sections: 1) lymph nodes, 2) collecting lymphatic vessels, and initial lymphatic vessels [1]. The initial lymphatic vessels (also known as lymphatic capillaries) use pressure gradients to absorb fluid and solutes from the surrounding tissue and then transport it along to the collecting vessels [2]. These lymphatic vessels are important in the context of cancer metastasis as they are known to be used as passages for cancer cells to move easily throughout the body [3]. To do so, solid tumors, such as those in breast cancer are known to indirectly increase the fluid pressure in the tumor microenvironment (TME) and secrete growth factors to encourage lymphatic vessel growth, known as lymphangiogenesis, towards the tumor [3], [4]. Lymphangiogenesis is believed to also be impacted by the increase in transvascular fluid flow into the vessel from the increased pressure [5]. One proposed hypothesis is that inhibiting lymphangiogenesis will prevent cancer cell dissemination through the lymphatics vasculature [6]. However, these capillary lymphatics are difficult study both in vivo and in vitro due in part to their thin walls, small diameter, and the fact that key lymphatic biomarkers were only discovered in the past 20 years [7], [8]. To better study these vessels, I contributed to the development of a 3D microfluidic device that is capable of recapitulating functional capillary lymphatic vessels and the microenvironment in which they exist. This model was used to study how local fluid mechanical forces and a known lymphangiogenic chemokine, vascular endothelial growth factor C (VEGF-C), co-directs lymphangiogenesis in comparison to static conditions.
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    Evaluating Visualizations Used in Communication of Life Cycle Assessment Results
    (The Ohio State University, 2024-12) Roussos, Jason; Gingerich, Daniel
    Life Cycle Assessment (LCA) provides insight into the environmental and human health impacts of processes and products like electric vehicles. However, the complexity of LCA results often leads to ineffective communication of key environmental impacts and hinders their interpretation, preventing non-expert audiences from making informed sustainability decisions. My study addresses these communication challenges by evaluating visualizations commonly employed in LCA results. Using A/B testing through a Qualtrics survey, my study evaluates four common visualizations seen in LCA results: (1) stacked bar charts, (2) unstacked bar charts, (3) pie charts, and (4) Sankey diagrams. My survey collected responses from a total of 172 participants from Ohio State University and local Columbus communities, which I analyzed. My findings offer insights into the effectiveness of the visualizations and identify those that best bridge gaps in understanding between technical experts and general audiences. Based on these insights, I developed a set of recommendations to make complex LCA results more accessible and support informed decision-making. These recommendations crafted are from the survey results, but they also follow common best practices in visualization design.
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    Crowd Scene Anomaly Detection in Online Videos
    (The Ohio State University, 2024-12) Yang, Kaizhi; Yilmaz, Alper
    The prevalence of surveillance cameras in public places has led to an extremely pressing need for effective position and crowd monitoring, as well as anomaly detection. This paper tends to exhibit an incorporated approach that combines state-of-the-art computer vision techniques for comprehensive crowd surveillance. The main features of this novel approach are summarized into four steps: (a) Object detection and tracking; (b) Geometric rectification for positioning; (c) Motion extraction; and (d) Anomaly detection. First, this uses YOLOv5's Convolutional Neural Network (CNN) model in making efficient detection of objects, focusing on spotting individuals within crowded scenes. After detection, a strong mechanism for tracking is established with the help of the DeepSORT algorithm, which can track the person across frames. It has to gain the people's position in the video frame and analyze motion data with the guarantee of capture of camera-scene geometry. Each frame thus gets converted from the 3D perspective to a 2D bird's eye view within the surveillance video, giving a guarantee of capture of the geometry of a camera scene. Motion anomaly detection is addressed through statistical methods, with Kernel Density Estimation (KDE) being employed to identify deviations from normal motion patterns. Extensive experiments conducted on different online crowd scene video datasets validate the effectiveness of the proposed anomaly detection mechanism. Overall, this integrated approach proposes a promising solution to crowd surveillance, further development of object detection, tracking, and anomaly analysis for monitoring public spaces.
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    Artificial Weather Forecasts with Realistic Uncertainty for Performance Evaluation of Home Energy Management Systems
    (The Ohio State University, 2024-12) Freund, Court; Stockar, Stephanie
    Home energy management systems (HEMS) and other demand side management strategies are necessary for the establishment of stable and sustainable energy grid. HEMS schedule the timing of deferrable loads within homes by minimizing energy costs according to a time variable price for electricity while maintaining occupant comfort. Scheduling these loads establishes a challenging optimization problem, in which the controller must handle significant operational uncertainty, including error in weather forecasts and load requests from residents. To properly evaluate HEMS performance, it is necessary to do so using conditions that accurately mimic realworld forecast uncertainty. However, there is a lack of open access historical weather forecast data, leading researchers to rely upon synthetic weather forecasts. This thesis aims to improve the accuracy of HEMS performance evaluation by generating synthetic weather forecasts with uncertainty that is more accurate to real-world conditions. Live weather forecast uncertainty was analyzed by recording data from an AccuWeather API and comparing to weather observations from the National Oceanic and Atmospheric Administration. A long-short term memory model was developed to generate synthetic weather forecasts with realistic uncertainty. This analysis showed that real-world weather forecast uncertainty is dependent upon time of day, location, and the lead time between a weather forecast and its prediction. While the model developed to generate synthetic weather forecast does not accurately match real-world uncertainty, it establishes a methodology which can be improved upon and implemented in future HEMS evaluation.
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    Intrafibrillar Mineralization of Type I Collagen: Biomimetic Methods and Microscopic Characterization
    (The Ohio State University, 2024-12) Murray, Jessica; Cho, Hanna
    Bone is a connective tissue that provides structural support throughout the body. Depending on location and external loading, bone adjusts its material properties to meet functional demands of the body. This is due to collagen in the bone acting as a soft organic material that can be strengthened through intrafibrillar and extrafibrillar mineralization. While intrafibrillar mineralization is known to occur in bone, the multiple factors which mediate the process are not clearly understood. The overarching goal of this research is to enhance understanding of how collagen mineralization strengthens bone, with a particular focus on the role of collagen piezoelectricity in the intrafibrillar mineralization of collagen. Achieving biomimetic intrafibrillar mineralization in vitro is a critical step toward this goal. To evaluate and confirm the effectiveness of this process, three consistent and repeatable biomimetic mineralization processes were applied to collagen sponges and self-assemblies, and their outcomes were analyzed using advanced imaging techniques. Three mineralization solutions were investigated, each using polyaspartic acid as the polyanionic peptide to create a polymer-induced-liquid-precursor (PILP) that crystallizes into hydroxyapatite. The first solution used rac-glycerol 1-phosphate and alkaline phosphatase, the second used a tris-saline buffer, and the third used crushed ammonium carbonate for vapor diffusion. Atomic force microscopy (AFM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) were performed to understand the extent of intrafibrillar mineralization for each process. Results from AFM, SEM, and TEM showed a clear picture of the control collagen samples with identified D-spacing for comparison with mineralized samples. AFM, SEM, and TEM results of the collagen sponge and self-assemblies for each mineralization method showed clear evidence of mineralization. Each of the three methods eliminated or reduced the appearance of D-spacing within the collagen fibrils, which is the main indication of mineralization. Of the three solutions investigated, the rac-glycerol 1-phosphate solution was the most effective at inducing intrafibrillar mineralization of the collagen self-assembly within 12 days, as shown by mineral crystals that formed within the collagen fibril. With continued work, this research will further the understanding of natural bone mineralization by providing the most effective standard and consistent process for biomimetic mineralization of collagen. Now that the rac-glycerol 1-phosphate solution has been proven to effectively mineralize collagen samples, this method can be used to produce different degrees of mineralization for further investigation into the effect of collagen piezoelectricity on intrafibrillar mineralization.
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    Effective Routing in Payment Channel Networks using Spanning Trees
    (The Ohio State University, 2024-12) Rustagi, Abhiram; Venkatakrishnan, Shaileshh
    In today’s world, the demand for cryptocurrencies is increasing, making scalability a significant challenge. Payment Channel Networks (PCNs) have emerged as a viable solution. However, PCNs still face challenges in routing payments effectively. Payments typically flow over a single channel in one direction, leading to channel depletion and failed trans- actions in that direction. Consequently, na ̈ıve routing schemes, such as shortest path routing, can exhaust critical channels and freeze the sys- tem. To address these issues, we present STR (Spanning Tree Routing), an algorithm that leverages the entire network and rebalances channel capacities dynamically. We are able to route large transactions over low- capacity channels while utilizing a larger portion of the network. Our experimental studies show that STR performs significantly better in net- work scenarios of low demand density, where traffic predominantly flows in one direction when compared with the shortest path algorithm. In such scenarios, STR algorithm provides performance improvement by a factor of 50 compared to the shortest path algorithm and also leads to fewer imbalanced channels.
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    Computational Modeling of Ion Channel Clustering in Cardiac Cellular Membrane
    (The Ohio State University, 2024-12) Aiello, Ross; Weinberg, Seth
    Ion channels are found to group into clusters in the plasma membrane of cardiac myocytes. However, the mechanisms behind clustering especially under disease conditions are not known. Studies indicate a strong link between altered ion channel expression and vascular diseases. Clustering behavior was analyzed in a computational model simulating ion channel insertion, removal, and diffusion. Thousands of simulations were ran varying parameters involved in clustering. Simulations were analyzed using averages, variances, histograms analyzing cluster distributions, and through visible clustering behaviors generated from the model. Parameters involved in clustering and the effects on clustering behaviors were compared. The study found that simple channel interactions are the most important for determining cluster properties in a cardiac membrane using a stochastic, self-assembly process. The model has implications for ion channel modeling under disease conditions. Additionally, the model could provide insight into how clustering behavior changes and provide novel techniques for therapies.
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    Material Analysis of Filament for 3D Printing of Poly(l-lactide-co-ε-caprolactone) (PLCL) for Implant to Track Breast Tissue Tumor Cavity After Lumpectomy
    (The Ohio State University, 2024-12) Einstein, Isaac; Metzler, Sandra
    After removing a tumor in a lumpectomy surgery, breast cancer patients undergo additional radiation therapy to kill any stray cancer cells and prevent the cancer from resurfacing. This additional radiation is highly targeted to avoid damaging nearby tissue. Once the tumor is removed, however, there are currently no products to adequately map the resulting cavity that requires additional radiation. Without a properly marked tumor cavity, radiation oncologists risk ineffectively removing all stray cancer cells. We aim to develop a device to track the cavity region in a 3D space on CT scanning to aid in radiation treatment planning. This will be done through the creation of a 3D printed biodegradable and eventually fully radiopaque implantable mesh. This research evaluated the material properties (Young’s Modulus, Yield Strength, and Bending Modulus) of the mesh material. A mesh was developed using a 3D printable Poly(l-lactide-co-ε- caprolactone) (PLCL) filament from an external vendor. Research will continue with an internally developed filament using powder-based raw materials. These research methods will be applied to the internally developed filament once created. As of now, only the externally sourced filament has been analyzed. Young’s Modulus (in tension) and Yield Strength were found by performing a tensile test on an Instron Universal Testing Machine. Bending Modulus was found using a 3-point bend test on a Mark-10 Bend Machine. These results showed that the tensile strength was roughly 20.929 MPa, the Yield Strength was 17.361 MPa, and the Bending Modulus was 369.620 MPa. These material properties are not well studied within breast tissue and thus cannot compare the PLCL-based device to the natural tissue it will be implanted within. Exploring this gap in literature paves the way as a comparison point for future devices. These measurements also serve as a benchmark to quantify the effects of adding a radiopaque agent to the implantable device. A fully radiopaque and biodegradable implant can improve on the shortcomings of current tumor marking practices.
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    Deep Level Defect Formation and Diffusion in Nitrogen-Annealed Ga2O3
    (The Ohio State University, 2024-12) Wu, Mingxuan; Brillson, Leonard
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    High Capacity Iron-poor Ferrites for Syngas Generation from Carbon Dioxide and Methane
    (The Ohio State University, 2024-12) Tomechko, Michael; Zhai, Shang
    Carbon conversion will play a critical role in preventing global average temperatures from surpassing 1.5-2°C above pre-industrial levels. Dry reforming of methane converts carbon dioxide and methane into syngas (CO + H2), an important building block for the production of liquid fuels, ammonia, methanol, and steel. However, no commercial processes exist for dry reforming of methane mainly because of catalyst deactivation via carbon deposition and the high cost of noble-metal-based catalysts. Chemical looping technology decouples the dry reforming of methane into two steps: methane reduction of a metal oxide, and carbon dioxide splitting by the reduced metal oxide. Ferrites are a common type of oxide material in chemical looping known for their high oxygen exchange capacity and low material cost. Iron is usually the major active redox element in ferrite materials such as NiFe2O4, but recent thermodynamic modeling results have predicted that iron-poor ferrite materials have greater oxygen exchange capacities than traditional iron-rich ferrites for dry reforming of methane. Here we present the first experimental demonstration of this counterintuitive oxygen exchange capacity dependence on ferrite iron ratio in chemical looping dry reforming of methane. Thermogravimetric analysis was conducted on supported Co-ferrites of various Fe ratios for isothermal dry reforming of methane at 700°C. As predicted by the theoretical models, iron-poor ferrites exhibited greater oxygen exchange capacities than iron-rich ferrites. Additionally, using ZrO2 as a support material was found to maximize chemical reaction kinetics without inducing carbon deposition. These findings contribute to future materials design and scale-up for high capacity and energy efficient chemical looping dry reforming processes.
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    Curbing Sediment: Controlling Stormwater Pollution using a Novel Curb and Gutter Design
    (The Ohio State University, 2024-08) Schuellerman, Henry; Winston, Ryan
    As urbanization occurs, the increase in impervious surfaces, soil compaction, and removal of vegetation reduces the infiltration capacity of soils, reducing groundwater recharge. Urban runoff causes many water quality concerns and environmental issues, including stream erosion, pollutant transport, and flooding. With respect to water quality, transport of nutrients, metals, sediment, micropollutants, and emerging contaminants by stormwater is an urgent challenge in urban areas worldwide. Stormwater control measures (SCMs) are often implemented by municipalities to curtail these negative impacts on water quality; however, infiltration-based SCMs may become clogged with stormwater-borne sediment over time, greatly reducing their efficacy. Thus, pretreatment devices, such as forebays, filter strips, catch basin inserts, or hydrodynamic separators are implemented upstream of these SCMs to remove sediment and lengthen maintenance intervals. In the urban built environment, space constraints make retrofitting SCMs into existing development difficult and the installation of pretreatment measures even more challenging. Thus, new pretreatment systems need to be developed which fit within the existing road right-of-way. A modified curb and gutter system was designed and tested at laboratory scale; roughness was added to the curb and gutter, with varying degrees of spacing, shape, and depth of indentations, with the intention of reducing the water flow velocity and trapping sediment particles. The best performing designs removed >80% of sediment in simulated stormwater at the laboratory scale. In the current research, the most effective gutter roughness design was selected and implemented on a 60-meter section of Carmack Road on Ohio State University’s west campus. By using the standard curb and gutter on the opposite side of the street as a control for the experiment, we evaluated the performance of this modification. Effluent samples from both the treatment and innovative curbs were collected using automated samplers and tested for nutrients, metals, and total suspended solids (TSS) concentrations to understand real-world benefits of this novel pretreatment. Curbing Sediment provided no significant reduction in pollutant concentrations (TSS, nitrogen and phosphorous species, or trace metals); however, it is suspected that bare soil created by the construction process located adjacent to the treatment curb, impacted the results. Curbing Sediment tended to have lower concentrations of pollutants (compared to the control) in the final 4 months of the study, suggesting that a start-up effect may exist. Thus, continual site monitoring for an additional several months beyond what is presented in this thesis is recommended to holistically evaluate the effectiveness of Curbing Sediment.
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    Autonomous UAV Swarms: Distributed Microservices, Heterogeneous Swarms, and Zoom Maneuvers
    (The Ohio State University, 2024-05) Angueira Irizarry, Kevyn; Stewart, Christopher
    Over the last few years, precision agriculture has greatly benefited from advancements in Unmanned Aerial Vehicles (UAVs). UAVs used in crop map ping allow farmers and researchers to tailor farming practices to the specific needs of individual management zones. Yet despite their benefits, traditional exhaustive approaches to UAV remote sensing are constrained by the low battery capacities of UAVs. To optimize battery usage, we present our work across 3 papers on alternative reinforcement learning (RL) and multi agent reinforcement learning (MARL) approaches to UAV remote sensing, namely: SoftwarePilot 2.0, heterogeneous swarms, and the Zoom maneuver. Starting with SoftwarePilot 2.0., we introduce a software package that sup ports scalable autonomous UAV swarms through microservice model design, container deployment technologies, and specialized MARL policies. These improvements to SoftwarePilot 2.0. reduced energy costs by 50% and improved swarm decision-making by 2.1 times from base SoftwarePilot. Moreover, we further explored multi-agent strategies through the extrapolation of multiple health metrics with heterogeneous UAV swarms. Heterogeneous swarms can capture data from multiple types of sensors, e.g. RGB, thermal, multi-spectral, and hyper-spectral cameras, and then extrapolate for various distinct health metrics across the whole field. Our preliminary results showed 90% accuracy from extrapolation from sampling only 40% of the field. Lastly, we proposed a study on the battery and accuracy tradeoffs of Zoom maneuvers. Moreover, Zoom maneuvers or changes in altitude trade battery for increased local accuracy. Our study considers the computational battery cost and flight battery cost tradeoffs of autonomous vs. RL implementations of Zoom maneuvers. Ultimately, this paper provides new insights into the execution and performance of various autonomous and multi-agent UAV remote search strategies.
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    The Effect of Electrostatics on the Trajectory and Adhesion of Dust Particles in Jet Engines
    (The Ohio State University, 2024-05) Sabau, Tanner; Bons, Jeffrey
    Despite the continued advancements in jet turbine engines to be more efficient and run hotter, foreign object damage (FOD) still poses a large problem and can negate some of the improvements. Extensive research has been done on how FOD such as dust particles can impact cooling holes and build up within engines over time, but there has been limited research on the influence of electrostatic forces on these particles. This research aimed to investigate how electrostatics from the atmosphere and tribocharging affect the trajectory and adhesion of dust particles within jet turbine engines. Three tests were conducted: a vertical drop test within a uniform electric field, an angled drop test on a charged plate, and an impingement cooling deposition test using a charged target. In the vertical drop test, 0-20µm Arizona Road Dust (ARD) was dropped through an electric field 90cm tall and 10cm apart. Mass fractions were collected on different sections of the electric field to determine alterations in the particles’ trajectory. The angled drop demonstrated the influence of charge on the tested dust’s adhesion strength by dropping the 0-20µm ARD on a 10° tilted, 90cm tall, charged plate. The impingement cooling deposition test simulated engine conditions, with 0-10µm ARD blown through a narrow tube at high velocity and temperature impacting a charged target. The results indicated that at low speeds the electric field significantly influenced the ARD trajectory, with smaller particles more affected than larger particles. Increased voltage in the angled drop test correlated with larger deposits at the top of the plate, which showed higher adhesion strength of the dust. Surprisingly, higher plate voltage in the impingement cooling deposition test led to decreased dust accumulation in the region of interest. By exploring dust behavior within engines under electrostatic influence, these findings will open new possibilities for enhanced engine performance and durability.
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    Metabolic Cost of Overground Walking Using a Motorized Walker-like Exoskeleton
    (The Ohio State University, 2024-05) Hu, Jasper; Srinivasan, Manoj
    Those with movement disorders commonly use exoskeletons and assistive walking devices. The purpose of most exoskeletons and assistive walking devices is to reduce the effort required to perform a task by providing mechanical assistance to the user. A way to measure effort is by studying metabolic cost. Thus, by providing mechanical assistance when performing a task, the metabolic cost of performing the task may decrease. Previous studies showed a passive walker-like exoskeleton cart in some configurations decreased the metabolic cost of walking [1]. Since such findings, a brushless DC motor was added to the cart to provide an adjustable assistive forward force on the user while walking. This research aims to determine the relationship between the intensity of the assistive forward force, metabolic cost, and walking speed when overground walking with the cart. To do so, metabolic and walking speed data was collected from five subjects using a COSMED K5 system and a video camera respectively. Each subject completed ten six-minute trials where nine of the trials were used to collect walking data. The trial order was randomized. One of the trials was used to collect normal walking data in which the subjects walked normally, without the cart. The metabolic cost and walking speed from this normal walking trial were used as the baseline metabolic cost and walking speed during data analysis. When averaging across the five subjects, the cart was shown to decrease walking speed for all but the greatest assistance level (potentiometer setting 4.2, corresponding to large assistance). The cart increased the average metabolic cost per unit time from normal walking for all assistance levels except one (potentiometer setting 3.6, corresponding to medium assistance) and increased the average metabolic cost per unit distance from normal walking for all assistance levels. However, analyzing the data subject-wise, we found that the cart decreased metabolic rate below normal walking for four out of the five subjects and that the cart decreased the metabolic cost per unit distance for three out of the five subjects (with one subject showing a marginal increase). These decreases suggest that the cart may be promising. Further research will be required to determine how the cart can be modified or how much training the subjects need to be provided such that the cart becomes a more uniformly assistive walking device. Should the cart be modified and proven to reduce the metabolic cost of walking, the cart may replace other devices and provide a framework for future device designs.
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    Illuminating Neural Pathways: Modulating Motor Cortex and Related Pathways with Photobiomodulation
    (The Ohio State University, 2024-05) Yu, Emily; Saygin, Zeynep
    Parkinson’s Disease (PD) and Major Depressive Disorder (MDD) are prevalent disorders of the brain which may benefit from treatment via nonpharmacological neuromodulation. Current approaches include transcranial magnetic stimulation (TMS) which has been shown to noninvasively stimulate the brain with transient effects. However, the effects of TMS are limited to superficial regions. A newer noninvasive method that can reach subcortical structures is transcranial photobiomodulation (tPBM), which uses visible to near-infrared light to stimulate neurons. In this work, we have built a multi-wavelength tPBM system to assess the effects of light of 1064 nm wavelength on brain activity and connectivity. Given that motor skills are affected by MDD and PD, we focused on stimulating the primary motor cortex (M1). Healthy adult volunteers (N=10) underwent four sessions of stimulation consisting of active tPBM and TMS along with respective sham sessions. Structural and task fMRI were taken before and after stimulation. Participants performed a motor task to explore the effect of stimulation within each individual’s motor cortices. Here we report that tPBM successfully stimulated M1 to a similar amount of activation as TMS in a safe and short-term manner. The effects of tPBM and TMS stimulation on motor activation was not significantly different within participants, suggesting that the two types of stimulation induce similar effects on the somatomotor cortex. We also observed significant changes in functional and structural connectivity between the motor cortex and thalamus after PBM stimulation. These results are in line with previous literature. Interestingly, TMS stimulation did not seem to affect structural and functional connectivity. Our preliminary results reveal that tPBM can cause changes in activation and connectivity of the somatomotor cortex with short-term effects that are comparable to the gold standard of neuromodulation, TMS. tPBM is still a relatively novel technique with more to be explored. PBM harnesses the neuroprotective properties of brain cells and may be useful when pharmacological options are unsuccessful or cannot be tolerated. Compared to other stimulation methods, PBM can penetrate further into the brain, providing more options for treatments of mental illnesses.
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    Development of Cathode Catalysis for Co-Electrolysis of CO2 and H2O
    (The Ohio State University, 2024-05) Lvovich, William; Ozkan, Umit
    The increase in CO2 emissions and the strained future energy capabilities of fossil fuels have driven research to focus on sustainable energy. To address these alarming issues, high-temperature co-electrolysis of CO2 and H2O conducted within a solid oxide electrolysis cell (SOEC) can be utilized. It not only reduces the amount of CO2 in the atmosphere, but also generates usable synthesis gas (H2 and CO). This synthesis gas can be further processed into light hydrocarbons via Fischer-Tropsch synthesis. Therefore, it is evident that improving the SOEC is of upmost importance. In this study, the double perovskite cathode catalyst Sr_(2-x)Fe_(1.55)Mo_(0.45)O_(6) (SFM) will be investigated for its high electronic and ionic conductivity, which is ideal for the co-electrolysis of CO2 and H2O at high temperatures. The study will highlight various permutations of the base SFM via A-site deficiency and nickel and cobalt doping, which improve the electrical conductivity and the chemical activity. The proposed study will centralize on developing a cost-effective, chemically active catalyst for the aforementioned electrolysis reactions to ensure SOEC’s will become a viable economic competitor in the marketplace.
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    Numerical Investigation and Optimization of a Miniature In-Pipe Hydropower Turbine
    (The Ohio State University, 2024-05) Lenk, Charlie; Belloni, Clarissa
    Pico hydropower energy generation, an emerging field in renewable technology, has faced limited funding and attention in the past due to the inherent lower efficiencies found for smaller scale turbines. This research addresses the need to provide a small amount of power in situations where consistent power availability and water quality may be a concern. Specifically, this research numerically investigates the performance of miniature turbine designs suitable for integration within water piping of facilities or homes to provide enough wattage for UV LED water disinfection at the point of use (POU) scale. Aiming to maximize the energy extracted from water flowing at POU water pipe pressure and flow rates, this study conducts Computational Fluid Dynamics (CFD) analysis. This research evaluates the hydrodynamic performance of a pre-manufactured turbine. After this, changes to the nozzle geometry were made in an attempt to improve efficiency. After varying the height of the nozzle, a max hydraulic efficiency of 22.05% was found at a flow rate of 2.2 GPM and a runner rotational velocity of 2200 RPM. The results suggest that further numerical analysis of various changes to the turbine geometry would be useful. A more complete nozzle geometry parameterization study is recommended as the next optimization step. Changing the runner hub size, and the number of blades on the runner is another recommended course of action. Once a promising novel geometry has been identified, the Hydro and Aero Energy Group (HAEG) will continue with producing a physical prototype of a POU miniature hydropower turbine.
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    Developing a Sensor Calibration Device for Sensory Brain Computer Interfaces
    (The Ohio State University, 2024-05) Terveer, Michael; Lucas, Timothy
    Brain Computer Interfaces (BCIs) provide individuals with severe neurological conditions the ability to regain functions they have lost, such as movement and speech. Significant research with these BCI systems has been performed specifically in spinal cord injury patients in an effort to create methods for restoring motor functions to patients. A lack of knowledge, however, exists in creating BCI systems that can naturally restore sensory function in such patients. New implantable fingertip force sensors have been developed that could provide patients the ability to regain this crucial function of the nervous system. These novel sensors, however, require calibration with commercial sensors to be effective and useful for different patients who require their own unique stimulation parameters. This project aimed to create a first-generation (“alpha”) prototype of a calibration apparatus for these sensors for specific patient scenarios as well as test and validate the prototype in a real patient setting. Following the design, prototyping, and validation process, a modular, custom forearm cradle device was created and proven to be capable of registering force outputs in a clinically relevant setting. A production process was created along with the first iteration of the cradle, permitting the expansion and tailoring of this process for usage in several different patients. Furthermore, the function of the device in registering the force outputs of patients’ hands was verified in four healthy volunteer subjects. This was accomplished using the commercial sensors selected for verifying the custom sensors against. Results showed that force outputs could be distinguished based on the time duration of force applied, the magnitude of strength applied, the location of force application, and ultimately the individual applying the force. These initial results confirm the need for the patient-specific calibration setup that has been developed in this study.
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    High Temperature Oxidation of Refractory High Entropy Alloys (RHEAs) and the Use of High Entropy Rare Earth Oxide (HERO) Coatings
    (The Ohio State University, 2024-05) Marino, Isabella; Locke, Jenifer
    Refractory high entropy alloys (RHEAs) possess favorable material properties, such as high melting points, resistance to corrosion, microstructural stability, and mechanical strength, which makes them a strong candidate for aerospace, automotive, and nuclear applications. To ensure safe high temperature performance, understanding and minimizing the rate of oxygen diffusion, and specifically high temperature oxidation, in RHEAs is imperative. The inherent high temperature oxidation performance of two RHEA compositions provided by the United States Air Force Research Laboratory are being investigated, after varying high temperature exposures in a controlled oxygen environment for various time intervals. Additionally, the effects of surrounding each alloy in a high entropy rare earth oxide (HERO) sintered powder sheath provided by the University of Virginia is investigated under identical conditions. Dilatometry is used to compare thermal expansion between the substrates and HERO coating. Thermogravimetric analysis is used to measure oxidation resistance and SEM and X-ray techniques are used to understand the microstructure.
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    A Techno-Economic Analysis of Lithium-Ion and Sodium-Ion Battery Energy Storage Systems in Buildings with Renewable Energy Sources
    (The Ohio State University, 2024-05) Casey, Austin; D'Arpino, Matilde
    Battery energy storage systems (BESS) provide various benefits, including renewable energy integration and grid support ancillary services, such as frequency regulation. The most commonly dispatched BESS are those of Lithium-ion (Li-ion) chemistries. However, concerns relating to depleting Lithium reserves as well as ethical issues relating to the extraction of Lithium and associated materials have provided motivation to search for a sustainable battery chemistry that can provide comparable, if not better, performance than Li-ion. An emerging technology of interest that may address this issue is the Sodium-ion (Na-ion) battery, due to the vast abundance of Sodium in nature and theoretical performance being similar to its Li-ion counterpart. In this Thesis, a techno-economic analysis of Li-ion and Na-ion BESS have been performed to determine their performance and financial metrics. The Energy Advancement and Innovation Center (EAIC) has been used to model a building with renewable energy resources, and a BESS of each chemistry has been designed to meet the optimal dispatch strategy to meet the load demand of the EAIC as determined by the Renewable Energy Integration and Optimization Tool (REopt) provided by the National Renewable Energy Laboratory (NREL). The financial metrics of each BESS have been obtained using the cashflows from REopt to determine the net present value (NPV) of each project. Then, using the power profile from REopt as an input, an electrothermal simulation for grid-connected storage has been developed to determine the performance metrics of each BESS chemistry. To simulate the performance metrics for frequency regulation, a RegD signal from PJM was used as the power profile for each BESS. The financial metrics of each BESS performing frequency regulation were obtained by calculating the credits using data from PJM. Finally, a comprehensive comparison of each technology has been provided for each BESS chemistry, accounting for its performance and financial metrics, while also considering the social and environmental impact of each technology.