Water splitting is important to a green energy future. Current issues with efficient water splitting include degradation of the fuel cell materials, thermal expansion, and transport through the material. Precise control of nanomaterial composition and morphology are among a materials scientist's tools to design novel low-cost and efficient materials. One way to improve material performance through controlling the composition is to create a high entropy oxide. There has been great interest in high entropy oxide systems because of the ability to combine multiple well-performing cations into one oxide phase, taking advantage of the synergistic effect. This work focuses on Ba, Sr, Ca, Co, Fe, and Mn cations (promising candidates for solid oxide fuel cell electrodes) in the perovskite ABO3 structure. Controlling the synthesis method to achieve single-phase, high entropy materials and maintaining nanomorphology will be discussed in this presentation. Aerogel synthesis is done in an autoclave with pseudo supercritical fluid drying, which allows immediate departure of the solvent and promotes nanomaterial production, resulting in a dry powder. However, subsequent calcination steps to achieve a single-phase oxide often sinters the materials, which removes the desired morphology. Different morphologies are of interest to be used in solid oxide fuel cells because it may improve performance depending on the unique surfaces that are exposed with different free energies.

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.

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.

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.

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.

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.

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.

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.

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.

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.