Recent Submissions

  • Classifying pulse shapes from superconducting tunnel junctions for the BeEST experiment

    BeEST Collaboration; Taylor, John; Leach, Kyle G.
    The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment aims to detect physics beyond the Standard Model by measuring atomic recoils from the electron capture decay of Beryllium-7 (Be-7). The experiment utilizes Superconducting Tunnel Junction (STJ) sensors to measure the daughter recoil kinetic energy spectrum to search for neutrino-coupled Beyond-Standard-Model physics. This work presents systematic studies that aim to distinguish between events occurring in the top and bottom electrodes of the STJs to search for the presence of a line-splitting artifact that could mimic a heavy neutrino signal. This is accomplished by analyzing the rise and fall times of the electrical pulses generated by the nuclear decays. Two primary techniques, 10-90% Rise Time Analysis and Charge Integration, are employed to investigate the pulse characteristics. While the former exhibits challenges in noise and pile-up events, the latter reveals a clear separation in the data, indicating a splitting effect caused by the STJ detector or the data acquisition system. The study proposes further investigation into the segregation observed and explores alternative methods for event separation.
  • Fluorescent point tracking for optical encoding in near-field ptychography

    Masztalerz, Veronica; Mubeen, Nabeeha; Selman, Beau; Adams, Daniel
    Ptychography is a process that utilizes scattered light patterns to image an object. To perform ptychography, an optical stage is employed to shift an object relative to a laser, often in hundreds of discrete positions. Keeping track of this motion involves a system of encoding the stage's position at each shift. This research focuses on optical encoding by tracking the motion of a fluorescent point adjacent to the stage. By imaging the fluorescent point at each position along with computing a cross-correlation with prior positions, information about the fluorescent point's relative position is calculated. Thus, the difference between highest-intensity positions at each stage motion represents the length traveled by the stage, effectively encoding its movement.
  • Optimizing shallow geothermal energy

    Neuder, Camille; Florida, Mark
    This project focuses on using shallow geothermal energy to provide clean and optimal energy to a 2000 square foot house test site in Dodge City, Kansas. The described test site aims to maintain a consistent temperature of 70°F year-round, 24 hours per day, using the most efficient methods of geothermal energy for the local environment. The identified solution involves a vertical loop with an open-source pumping system from the local aquifer connected to a heat pump. The results demonstrate that cooling can be effectively managed with circulating water from a shallow aquifer, while heating to 70°F requires supplemental energy due to the aquifer's temperature of 60°F. The mechanical and heat transfer process design can be adapted to provide efficient heating and cooling to multiple houses, facilitating an expansion from individual residential use to neighborhood access by connecting houses with horizontal loops. The analysis techniques used in this study can be extrapolated to any location, considering that each location will have different temperature profiles and aquifer depths to extract heat and cooling mediums.
  • Reconstructing ultra-high-energy cosmic ray cascades with deep learning

    Woo, Nathan; Wang, Zhuoyi; Mayotte, Eric; Mayotte, Sonja
    Ultra-high-energy cosmic rays are single atomic nuclei from other galaxies and the most energetic phenomena known to humankind. In observing these and using them to increase our astrophysical understanding, two properties are of key importance: the particle's energy and its mass. When one of these particles strikes the top of the atmosphere, they are destroyed and create a high-energy particle cascade which can reach 10 billion particles in size. Here, we present a new machine learning method to maximize the amount of information that can be extracted on the mass of the ultra-high-energy cosmic ray. We find that a neural networks such as a convolutional neural network can improve the mass prediction of ultra-high-energy cosmic rays, with a proton-iron merit factor of 9.81, three times better than traditional solutions. The extra precision on mass reconstruction for these cosmic rays can lead to a revolution on the quality of astrophysics performed with current ground-based observatories, and displays the usefulness of machine learning techniques in astrophysics.
  • Fabricate mesoporous silica nanoparticles with iron core for transporting organometallic cataysts and exogenous enzymes

    Raizada, Rewa; Kovach, Nolan C.; Smith, Jaclyn; Trewyn, Brian G.
    The objective of this research is to design and fabricate multifunctional mesoporous materials with an iron core to hold and transport paramagnetic molecular catalysts and biocatalysts that are capable of synthesizing advanced molecules in intracellular environments. Mesoporous Silica Nanoparticles (MSN) have a large surface area and can be used as drug carriers. Amine functionalization of MSN helps with dispersion, while paramagnetic component can assist in directed drug delivery under external magnetic field. Two distinct methods were employed for the manufacture of the nanocarriers: a co-precipitation and a solvothermal method. Both methods resulted in high surface area material with ordered, uniform pores. We will discuss the findings and material properties of both types of materials along with discussing applications for magnet-responsive mesoporous materials.
  • Machine learning as a tool to understand and predict ankle sprain

    Szigeti-Larenne, Jordan; Mazur, Mykola; Petrella, Anthony
    Ankle injury is a fundamental and recurring issue in high impact activity that affects athletes, military personnel, and everyday people. Current attempts at ankle injury mitigation look towards passive devices that simply support the ankle through bound structure built through the device. The goal of this study was to identify the risk factors and indicators that are actively associated with ankle sprain, implement them into a machine learning algorithm, and establish a program that could significantly predict ankle sprain. The currently understood risk factors were distinguished through previous research papers and were used as key features for the machine learning algorithm. Based on these features machine learning algorithms were used to predict ankle sprain. This preliminary research sets the stage for future research into wearable devices that could be implemented into a passive ankle brace and predict sprain while in motion. This prediction could then be implemented into active devices that will increase the stiffness of the brace only when sprain is likely.
  • Identification and analysis of two-pixel correlated events in BeEST Phase-III data

    BeEST Collaboration; Lamm, Amii O.; Leach, Kyle G.
    The Beryllium Electron Capture in Superconducting Tunnel Junctions (BeEST) experiment measures Lithium-7 atomic recoils from the electron capture decay of Beryllium-7 as a precision search for neutrino-coupled BSM physics. Following the single-pixel demonstration in Phase-II, Phase-III uses a 6x6 grid of superconducting tunnel junction (STJ) detectors, allowing us to analyze spatial correlations and simultaneity between devices. Due to the sensitivity of the detector, there are external events that must be identified and filtered out for the creation of the final Phase-III limit. In this talk, we present a systematic analysis of two-pixel correlated events for their location, time, energy and pulse shape to identify anomalous events and hypothesize their origins. By examining the shape and occurrence of these events, we can understand and reduce systematic uncertainty in our data and contribute to the design of the Phase-IV detector array.
  • Engineering surface properties through controlled radical polymerization for therapeutic application

    Kani, Wakana G.; Humpal, Adam; Kumar, Ramya
    Polymers play an integral role in therapeutic applications, especially in the development of drug delivery systems. Advancements in controlled polymerization have allowed for a greater control of polymer architecture. This work explores the atom transfer radical polymerization (ATRP) of hydrophobic polymers in alcohol-water media to find reaction conditions balancing an increased reaction rate while maintaining consistency and stability. The rate of polymerization was tuned by adjusting reactant ratios, altering the rate of radical formation and deactivation. Different solvent properties were studied as ATRP relies on water for a controlled reaction, necessitating a delicate balance with the alcohol required to solubilize the monomer. More protic solvents were shown to increase the reaction rate, but resulted in decreased control due to a higher probability of termination events. After successfully developing optimized reactions, the work is translated to polymerization on nanoparticles for drug delivery applications. The effects of pH and ion concentration on polymer swelling are studied through film characterization using dynamic light scattering (DLS) and zeta potential, measuring the changes in film thickness and surface charge.
  • Remote S-parameter communication from NanoVNA v2

    Hora, Kenny Y.; Elsherbeni, Atef Z.; Aaen, Peter H.
    Measurement of biological metabolites, such as glucose and lactate are important in both healthcare and athletic settings. Research is currently being conducted on remote sensing approaches to these metabolites, many of which use on-body antenna or resonator circuits that measure changes in resonant frequencies to determine the concentrations of the metabolite. However, these approaches use conventional laboratory VNAs, which are impractical for on-body measurement of moving subjects due to their size. A software program was developed for a small handheld vector network analyzer (NanoVNA) that allows it to be attached to a single-board computer and attached to the subject being measured. This permits the subject to move freely while measurements are wirelessly transmitted to a base station where they can be further analyzed.
  • One-pot synthesis of mesoporous cobalt phosphate used as a catalase-like nanozyme

    Hughes, Davin V.; Berstler, Calvin; Trewyn, Brian G.
    Being able to conduct multi-step chemoenzymatic catalysis in a one-pot system is a challenging task. A chemoenzymatic reaction represents a reaction where two or more consecutive transformations take place in a single reaction vessel. This process uses both enzymatic and chemical catalysis to more efficiently generate desired products from commercially available starting materials while removing the need to isolate intermediates. With new techniques to support employing enzymes and organic species within single-pot systems, the use of catalytically active mesoporous nanomaterials as enzyme supports has the potential benefits to enhance the performance of chemoenzymatic tandem systems. There are numerous advantages to using enzymes though they are costly and their functionality is limited to a small range of temperatures and pH levels. Because of this, enzyme mimics (Nanozymes) are very sought-after inorganic alternatives that are low-cost, high-stability alternatives. Here I explore a low-cost, high-efficiency method to synthesize a mesoporous cobalt phosphate (mCoPi) with the ability to transform hydrogen peroxide into water and oxygen and to be able to act as a catalase-like nanozyme in a variety of harsh local environments.
  • FEA ankle model to analyze ligament load and preventitive braces

    Kephart, Maximalian; Mazur, Mykola; Petrella, Anthony
    In the United States 25,000 ankle sprains occur every day where inversion sprains make up 80% of all ankle sprains. Inversion sprains structurally have the potential to affect three ligaments: the anterior talofibular (ATFL), calcaneofibular (CFL), and posterior talofibular (PTFL). The ATFL is the weakest ligament by far where 70% of lateral ankle sprains only involve this ligament. An ankle brace's goal is to take on the majority of the structural load that would be otherwise put onto the ligaments; moreover, in inversion sprains the brace needs to specifically protect the ATFL. The purpose of this study was to develop an FE model that uses external 3D scans to quantify the effectiveness of different ankle brace designs by analyzing the forces along the ligaments caused by an inversion sprain. Four simulations were analyzed, three of which used a 23 N-m moment applied on the ankle, foam brace, and plastic brace while the fourth simulation used a 46 N-m moment on the plastic brace. After applying a 23 N-m moment onto the ankle, the foam brace reduced the load on the ATFL by 51% and further reduced by the plastic brace by 80%. The significance of this study is the development of an FE model that can be applied to individual users to aid the design of custom fitting ankle braces while measuring this design's effectiveness in protecting the ATFL, CFL, PTFL, and preventing ankle inversions.
  • Autonomous lunar landing site preparation - testbed gantry components

    Lee, Thomas; Petruska, Andrew
    Mines has been contracted by NASA as part of the Lunar Surface Technology Research -- Autonomous Site Preparation: Excavation, Compaction, and Testing (LuSTR-ASPECT) Project, whose ultimate goal is to design and prototype an autonomous robot that can prepare a spacecraft landing location on the Moon. Once constructed, the robot will require a simulacrum of the Moon's surface for testing purposes. In addition to a large "sandbox" containing a lunar regolith simulant, the testing environment includes an XY gantry system to carry the robot's power cord during the testing period. During this research period, we utilized SOLIDWORKS computer aided design software to design two major components of the gantry system -- the "truss movers" and the "cart". The "truss movers" are positioned under the gantry's crossbeam, carrying it along a set of V-tracks and enabling translation on the X-axis. The "cart" carries the robot's power cord and the gantry's electronic hardware and rolls along the length of the crossbeam, enabling translation on the Y-axis. Validation of the designs will be executed by building small-scale prototypes to test their performances and manufacturing processes. Completion of the components' designs has furthered the overall progress of the testbed, and construction will soon begin in the Earth Mechanics Institute.
  • Presence of millennial-scale climatic cycles during the middle Eocene climatic optimum

    Fox, Maddie; Slawson, Jake; Plink-Bjorklund, Piret
    The Eocene epoch (55-34 million years ago) witnessed a transition from a greenhouse to an icehouse climate, marked by rapid, extreme global warming events known as hyperthermals. These events, triggered by spikes in atmospheric CO2 concentration, offer insights into Earth's response to high-magnitude CO2 changes, crucial for comprehending modern climate shifts. One such event, the Middle Eocene Climatic Optimum, was a major climatic shift lasting approximately 500 kyr. Orbital forcers, most notably variations in the amount of solar irradiance reaching Earth, are believed to explain many of the observed climatic variations in both this epoch and others. Changes in orbital patterns are widely believed to explain cyclicities on the 20,000 to 100,000 year scale, while changes in solar irradiance have effects on the sub-1,000 year scale. However, little work has been done to understand the influence of orbital cycles of periods between these, in the millennial range. This study investigates Middle Eocene Climatic Optimum temperature proxies from Ocean Drilling Program sites, revealing a statistically significant 2500 ± 250-year cycle, identified as the Hallstatt cycle. Linked to a spin-orbit coupling of Jovian planets, this astronomical origin suggests that solar system chaos during this period played a role in abnormal climate patterns. Understanding such complexities enhances predictions about current and future climates by acknowledging the substantial influence of external factors on climate dynamics.
  • Evaluating website security: a study on content security policy implementation

    Fernandes de Oliveira, Isabella; Ren, Mengxia
    Content Security Policies (CSPs) are vital defenses against cross-site scripting (XSS) and unauthorized web resource manipulation. This study investigates CSP implementation across the top 100 websites listed in TRANCO, focusing on resilience to external manipulation. Our analysis reveals that over 50% of domains lack adequate protection against XSS attacks, despite CSP implementation. Vulnerabilities include the misuse of 'unsafe-inline' directives and reliance on white-listing-based policies over nonce-based alternatives. These findings highlight the need for a comprehensive CSP approach, prioritizing script and web control. Strategies to enhance website security, such as stricter CSP configurations, are discussed, emphasizing nonce-based strategies and comprehensive directive coverage.
  • Holistic approach for multi-drone data collection

    Diller, Jonathan; Han, Qi; Fellinge, Cody J.; Schanker, Corey; Barigala, Priestly; Moon, Ava
    Drones can be used as data mules to collect data from wireless sensors to mitigate issues found in traditional ground-based networks. However, there are many open challenges to address in this problem that our team has been working on. We have developed a physical testbed for experiments, performed data collection to determine limitations on range and amounts of data, implemented an energy model into ArduPilot, and optimized the energy budget for offline and online planning.
  • Understanding multi-functional materials through preparation and characterization of formate perovskites

    Hope, Andrew; Mozur, Eve
    Multi-functional materials have been studied intensively for the last few decades for their interesting, coupled physical properties, and wide variety of potential applications: including high-density multi-state digital storage and small-scale magnetic or electric field sensors. Multi functional materials are a class of materials in which the electric dipole (positive and negative ends of the molecule) alignment, and magnetic properties are coupled. Thus, generating an electric response when the material is in a magnetic field and vice versa. However, there are few materials that exhibit this multi-functional behavior. Additionally, out of the materials that have been synthesized, many are lacking characterization data. Therefore, it is challenging to develop structure-property relationships and design principles for multi-functional materials. Our goal is to develop a framework such that we can properly engineer these materials or find a relationship between the crystal structure to the magnetic and dielectric properties. To achieve this goal, we will make a series of these multi-functional materials to understand these structure-property relationships. Structural characterization such as x-ray diffraction will determine trends in material structure. We plan on using magnetometry and dielectric spectroscopy under applied field conditions to study the functional properties.
  • Monte Carlo modeling of sub-keV backgrounds in superconducting tunnel junctions from gamma-ray interactions for SALER@FRIB

    Borbridge, Keith W.; Leach, Kyle G.
    The new Superconducting Array for Low-Energy Radiation (SALER) experiment at FRIB aims to directly embed short-lived isotopes in superconducting tunnel junction (STJ) sensors to measure nuclear recoil energies from weak decay as a search for BSM physics. At these eVscale energies, small energy depositions from simultaneous higher-energy events (since as gamma rays) generate backgrounds which are important to understand. I will present the first Monte Carlo modeling using the test case of 137Cs decays where a 662 keV gamma-ray is emitted and deposits small energies in the silicon substrate of the STJ as a critical first step towards background characterization for SALER@FRIB.
  • Age influences muscle excitation during the five times sit-to-stand clinical test

    Beebe, Claire A.; Silverman, Anne K.; Miller, Michael F.
    Each year, 28-35% of people 65 and over have at least one injurious fall, which can limit mobility and reduce quality of life. The Five Times Sit-To-Stand (5xSTS) is a clinical evaluation of muscle strength and fall risk. However, the outcome of this assessment, time to completion, does not reveal muscle coordination or movement during the task. Evaluating muscle coordination is important to guide treatment and reduce fall risk. Thus, we compared lower limb muscle excitation with electromyography in younger and older adults during 5xSTS. Twenty-two (11 younger and 11 older) healthy adults completed a 5xSTS trial where they rose from a seat to a standing position and returned to the seat five consecutive times as quickly as possible. We compared integrated electromyography values for the leg and low back muscles as well as hip, knee, and ankle joint moments between groups with an unpaired t-test. Older adults required greater muscle excitation for the gluteus medius (p=0.025), lumbar paraspinals (p=0.014), rectus femoris (p=0.002), vastus lateralis (p=0.011), and tibialis anterior (p=0.038). Older adults took a similar amount of time to complete 5xSTS (p=0.473), indicating muscle compensations in this group. Older adults had similar or lower joint moments when compared to younger adults. Thus, older adults generated similar muscle forces as younger adults during 5xSTS, but required greater muscle excitation to achieve these muscle forces. Muscle excitation changes may affect energy cost and fall risk during sit-to-stand with aging. Understanding these changes can aid in developing rehabilitation treatments and muscle strength benchmarks.
  • Wireless Nano-VNA S-parameter monitoring for biomedical applications

    Elmiladi, Lisa K.; Aaen, Peter H.; Elsherbeni, Atef Z.
    The dynamic monitoring of biological metabolites, such as glucose and lactate, plays a pivotal role in healthcare diagnostics and sports science. Current research focuses on remote sensing techniques utilizing on-body resonant antenna or circuitry to track metabolite cxoncentrations through frequency variation. Traditional vector network analyzers (VNAs) used for this purpose are generally bulky and tethered, limiting their applicability for ambulatory subjects. This presentation introduces an innovative enhancement of a compact handheld VNA, the NanoVNA-H, custom-modified with integrated Wi-Fi and Bluetooth capabilities. This advancement eliminates the encumbrance of cables, enabling the VNA to be compactly mounted on a patient and permitting unimpeded movement. The system is designed to wirelessly relay measurement data to a remote base station for real-time analysis, significantly improving the practicality of continuous, on-body metabolic monitoring.
  • Determining polarity in ferroelectric materials using precession electron diffraction and cepstral analysis

    Brown, Colton; Mis, Allison; Holtz, Megan
    Understanding local crystallography is necessary for understanding ferroelectric behavior in materials. Key properties to know include lattice parameters, interatomic spacings, and polarity. One tool to learn these properties is scanning transmission electron microscopy (STEM), which can measure a diffraction pattern (kx, ky) at every scan position (x, y). This allows crystallographic properties to be investigated at the nanometer scale. However, diffraction signals can contain artifacts from sample thickness and mistilt. These artifacts may be suppressed with precession electron diffraction (PED), which has the additional benefit of increasing the number of reflections in the diffraction pattern. In this work, we perform analytical calculations to assess the efficacy of using PED combined with cepstral analysis to measure polarity in lead magnesium niobate-lead titanate (PMN-PT). Taking the Fourier transform of the logarithmically scaled diffraction pattern yields the exit-wave power cepstrum (EWPC) which yields interatomic spacings in the crystal. To extract polarity, we use the imaginary component of the transform which contains the antisymmetric information, which is called the exit-wave imaginary cepstrum (EWIC). The EWIC transform is improved by having more higher-order diffraction disks, which is possible through PED. It was found that PED improves the EWIC signal: as precession angle was increased from 0° to 0.5° to 1°, signal noise decreased and dipole moments were better resolved in scenarios with and without mistilt. These results indicate that cepstral analysis of real samples may benefit from PED.

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