Most space missions include a suite of instruments, one of which is a radiometer. This project focused on designing and building a radiometer to remotely measure an object’s radiation in the frequency range from 5 to 20 micrometers, accounting for variations in emissivity of the source. This project was supported by NASA’s “Here to Observe” program, which provided insight into design principles and teamwork under the guidance of instructors and Lunar Reconnaissance Orbiter (LRO) mission scientists. The design and construction of the radiometer followed NASA’s mission design framework. The radiometer’s design utilizes an infrared sensor and an adjustable aperture lens to capture and focus thermal radiation. A microcontroller board was used to process the sensor’s data, converting radiation readings into temperature. Considerations regarding the form factor and efficiency of the device were investigated, with the objective of creating a mountable radiometer that can reliably collect and store continuous measurements. We present some preliminary data taken with the radiometer prototype and discuss its performance and potential improvements. 

Bacteriophages (phages) are viruses that infect bacteria and exist in all corners of the world that target specific bacterial hosts. Through SEAPHAGES, a worldwide program where undergraduate students isolate and characterise phages, two phages were isolated from the campus of NMTech from a partly shaded flower bed where the soil was dark and moist. The phages, RustyBoy and Natasha, were isolated using the soil bacterium Arthrobacter globiformus B-2979. Both phages developed small plaques on A. globiformis; Natasha’s were clear, while RustyBoy’s were opaque. Through TEM, the phages were both identified as siphoviruses with a capsid head diameter (Natasha: 65.32nm; RustyBoy: 69.534 nm) and tail length (Natasha: 230.88nm; RustyBoy: 237.714 nm). These were sent to be sequenced by Illumina sequencing. The phages belong in the AW cluster, which are lytic siphovirus phages. The genome sequences of the two phages are similar (98% identity). They have a 3’ sticky overhang with a sequence of CGCCGGCCT and 51.4% GC content, and 90 genes have been identified; Rustyboy’s genome is 54635 bp long, and Natasha’s is 54436 bp long. However, in the 199 bp gap between the phages, there is a unique gene and an additional orpham in RustyBoy not found in Natasha. The closest relative of these phages besides each other is Sporto (92% identity to RustyBoy and Natasha). These results contribute to our understanding of the AW phage cluster and will contribute new information with the unique gene.

Our projects aims to create a prototype sleep monitoring system. The system will implement non-invasive sensors that will record the subjects vitals during sleep such as their temperature. The system gathers and stores information over time for the option of analyzing the collected data. The goal is to create sensors that minimally interfere with the subject's sleep, without sacrificing data quality. 

In the US alone, 10 million tons of glass are disposed of annually, only a third of which is recycled. By taking advantage of the pozzolanic nature of glass, being a silicate material, we can dramatically increase the volume recycled by using it to replace some of the cement in concrete. This has the added benefit of requiring less cement, the production of which is very carbon emissive. Previous studies have shown that with sufficiently small particles and low replacement volumes, the alkali-silica reaction does not occur, and the resulting concrete will be structurally sound. By testing higher weight replacements, we aim to create concrete that uses more waste glass than previously reported, while maintaining sufficient mechanical properties. Towards this end, we’ve replaced the cement in ASTM standard concrete with up to 50 wt% glass, limiting the maximum particle size to 45, 38, 32, and 25 microns. Testing showed, 20 wt% glass mixtures were stronger than traditional concrete, while 30%, 40%, and 50% mixes were weaker. Within the 20% mixtures, a maximum glass particle size of 45 microns produces both the strongest and most consistent concrete, making it currently the most viable mixture for glass recycling. 

The objective of this project is to design a steady state plastic waste delivery system to a pyrolysis chamber. This system will be able to feed plastic and wood solids of various particle sizes to the reaction chamber in a controlled, safe, and effective manner without entraining plastic particles in the exit stream or clogging the reactor. If this design is successful, it will allow green and plastic waste to be steadily converted into liquid fuel. 

This project focuses on atmospheric physics, specifically in atmospheric dynamics of the gas giant planets of our solar system. We worked with a general circulation model (EPIC) in order to better understand how vortices like Jupiter’s great red spot move. Our main goal was to better understand how the vertical structure of the atmospheric zonal winds affects the drift rate of the vortices. To do this, we altered a function in the model that controls how the winds change with height and ran several simulations with different vertical winds. We show that the vertical wind structure can change the propagation speed of the spots. Therefore measuring the observed propagation speed of the spots can be used to constraint the atmospheric dynamics below the visible cloud layer on these planets. 

Every religion has its own unique set of ethical codes that its followers are expected to follow. As a result, adherents develop their behaviors based on these sets of moral standards, which may impact how and where their money is spent. Religious identity, or lack thereof, may play a significant role in shaping consumer behavior. This study aims to analyze how religious identity impacts consumption patterns by examining the purchasing behavior of religious texts on Amazon. I plan to collect data on the top 100 bestselling religious texts across various belief systems, including Agnosticism, Atheism, Buddhism, Christianity, Hinduism, Islam, Judaism, New Age & Spirituality, and Occult & Paranormal. Key data points will include average ratings, the number of reviews, and the price of paperbacks. By averaging these metrics, this research will calculate averages to reveal consumer habits within these religious groups. The findings are expected to highlight varying consumption patterns, particularly among religions with similar doctrinal foundations. Ultimately, this study seeks to uncover insights into how religious identities influence economic behavior, providing a deeper understanding of the relationship between religious doctrines and consumer preferences. 

This study conducts a visual analysis of player engagement, review sentiment, and key in-game events in Helldivers 2 - a third-person shooter developed by Arrowhead Studios - over the course of a year. By overlaying major content releases - including expansions and Warbonds - with notable real-world events and pivotal in-game moments (e.g., the liberation of Malevelon Creek in The Second Galactic War) this research explores their impact on player activity and community reception. A comprehensive graphical representation will illustrate trends in player counts and review sentiment (both positive and negative) to present a clear and concise view of engagement patterns. Additionally, a correlation analysis will assess whether fluctuations in player numbers align statistically with shifts in review trends. Ultimately, this study aims to provide a historical perspective on the game's lifecycle, offering insights into how developer communication, content updates, and community-driven events shape player retention and overall reception. 

Harnessing nature's ingenuity, this research pioneers the development of a cutting-edge tilt-rotor VTOL UAV inspired by the Arctic tern (Sterna paradisaea), renowned for its unparalleled endurance and energy-efficient flight. By mimicking the tern’s wing morphology and flight dynamics, this study aims to revolutionize UAV performance in both maneuverability and efficiency. Using advanced geometric modeling and computational fluid dynamics (CFD) analysis, an optimal aspect ratio of 9 was identified, balancing lift and drag forces. A Careful evaluation of wing configurations with varying taper ratios and sweep angles allowed for precise emulation of the tern’s superior aerodynamic characteristics. The UAV’s innovative tilt-able rotor mechanism ensures seamless transition between vertical take-off and landing (VTOL) and fixed-wing forward flight. Aerodynamic analysis, structural optimization, and mission-based atmospheric data guided the determination of wing loading and airfoil selection. Stability analysis and CFD simulations further fine-tuned the design. This bio-inspired approach not only advances UAV performance but also paves the way for future innovations in autonomous navigation and payload integration, solidifying its potential for diverse and complex operational environments. The integration of advanced autopilot systems and sensors enhances adaptability for critical applications, including surveillance and search-and-rescue missions. 

Digital logic forms the foundation of modern technology, enabling the binary systems that power everything from communication signals to image displays and mathematical operations. One of the most versatile tools for implementing digital logic is the Field-Programmable Gate Array (FPGA)—a reconfigurable hardware device capable of executing custom logic designs using languages like Verilog. For this project, I utilized a Spartan-7 FPGA and the Vivado development environment to create two distinct implementations: a rudimentary computer capable of executing code and a reaction time testing circuit using an LED, 7-segment displays, and switches. This project was undertaken as an opportunity to explore FPGA programming and gain hands-on experience with both the hardware and software involved. 

Magnetic field loop antennas collect magnetic field data, using Michael Faraday's principle which states “the induced electromotive force (EMF) in a closed circuit is directly proportional to the rate of change of magnetic flux through the circuit”. In lightning research, magnetic field antennas have applications including the localization of cloud-to-ground strokes and the estimation of their current peak values. They are also used in conjunction with electric field measurements for better understanding of lightning processes. Electric and magnetic field waveforms are similar at large distances, but must be measured separately at close range, making having both measurements highly beneficial. In this project, a shielded loop magnetic field antenna is being built for use in lightning detection. The antenna will consist of two orthogonal 1 meter by 1 meter loops constructed using coaxial cable in PVC conduit. It will use a preamplifier circuit. This includes an integrator, which is necessary since the voltage induced is related to the time derivative of the magnetic field, and an amplifier, which enhances the signal. A prototype of the circuit is being constructed and tested using a function generator and oscilloscope, and a smaller prototype loop is being constructed from coaxial cable and tested with the circuit. The results from the prototypes will be used to develop the final antenna. The completed antenna will be tested for lightning detection at Langmuir. It will be used in combination with other sensors to improve lightning data collection and understanding by providing an additional set of data. 

For amateur astronomers, gaining useful information out of their observations is not straightforward due to inaccessibility of tools. The resources and practices needed by the general community to conduct meaningful research is not readily available. Our goal with this project is to develop an easily accessible tool that will allow the public to analyze night sky observations with a specialization in asteroid tracking, which includes automatic data processing and detailed procedural guidelines on efficient search methods. While building the groundwork for this project, we have experimented with manual image correction and panorama stitching, a technique that an average amateur astronomer would use inexperienced, and determined this method was inefficient for handling large data sets. As a solution, we have begun to create a Python-based program that can automatically process data to search for any anomalous motion from celestial bodies in astronomical images. This tool also allows for the plotting of the orbits of such bodies. As we continue working on this project, we plan to form a cohesive program which will seamlessly merge these tools together for the benefit of budding astronomers. 

Lithium-ion batteries (LIB) are increasingly common energy storage systems, with uses in the automotive industry, in large-scale electrical grid storage/stabilization, and in consumer products. LIBs must be evaluated as a Multiphysics problem involving chemical, electrical, and thermal processes. Energy storage is achieved through a lithium-ion chemical reaction which produces the desired electrical voltage potential and current flow and the undesired byproduct of thermal waste. Thermal analysis of LIBs in Ansys Mechanical and Fluent is used to gain an understanding of output and lifetime performance. Building a relationship between the thermal gradient and electrical performance of LIBs allows for battery optimization via a geometric perspective. By fixing the geometric and chemical configuration of a modeled LIB, multiple electrochemical approaches can be evaluated to determine the transient 3D heat generation and temperature contour response of the LIB. Electrochemical theories, like the Newman, Tiedman, CU, and Kim model, the Equivalent Circuit Model, and Pseudo-2D model, are compared against simplified heat generation processes like uniform transient heat generation of similar geometries. The comparison of the numerical simulation results produces repeatable thermal gradient profiles of LIBs. Leveraging these validated simulation results can provide avenues for LIB thermal optimization. 

ARACHNOID (A Robotic Approach to Camouflaged Habituation and Natural Observation in Diverse Terrain) is a bioinspired robotic system modeled after the Goliath birdeater tarantula (Theraphosa blondi), designed to replicate realistic arachnid locomotion through mechanical innovation. The robot features a multilayer 3D-printed body, with the lower layer housing an Arduino board, battery, and circuitry, and the upper layer supporting a mechanical leg system that mimics tarantula gait using elastic resistance, mechanical leverage, and DC motor-driven actuation. Each leg performs coordinated vertical and horizontal motions, guided by observed tarantula stride patterns. Elastic components are integrated to utilize the kinetic and potential energy stored in the elastic elements, reducing motor strain and improving movement fluidity and efficiency. Because the current prototype is too heavy to rely solely on its legs, two concealed wheels positioned beneath the cephalothorax and abdomen, with the front enabling steering and the rear providing forward propulsion, enhance directional control and mobility while alleviating strain on the leg mechanisms. Additionally, the prototype was intentionally scaled up to enable mechanical refinement before eventual future miniaturization and integration of the system into the shed exoskeleton of T. blondi. Ultimately, ARACHNOID is intended as a discreet, terrain-adaptive surveillance tool for wildlife research. The biological accuracy of its structure and movement will be evaluated by quantifying any observed behavioral changes in our live Pinktoe tarantula (Avicularia avicularia), named Patricia, in response to the presence of ARACHNOID. 

This study examines the ethical implications and inherent biases of AI language models in In‑Context Learning (ICL) by analyzing AI‑generated summaries of articles with divergent perspectives on the Afghan War. Fifteen articles—five each categorized as positive, negative, or neutral—were summarized by a state‑of‑the‑art language model using carefully structured prompts. Summaries were evaluated for accuracy, sentiment alignment, and bias indicators. Results demonstrate that while the model reliably captured overt positive and negative tones, it exhibited a consistent negativity bias when summarizing neutral content and often oversimplified nuanced arguments. These tendencies risk propagating misinformation and reinforcing one‑sided narratives, underscoring significant ethical concerns in AI‑mediated information dissemination. Key contributors to bias include imbalanced training data and prompt sensitivity. To mitigate these issues, we recommend diversifying training corpora, implementing real‑time bias detection mechanisms, and establishing robust ethical frameworks—complete with transparency reports and regular audits—for AI deployment in sensitive domains. This research highlights the necessity of addressing AI bias to ensure fair, accurate, and responsible summarization practices in ICL applications. 

In the summer of 2024, Langmuir Laboratory restarted its rocket-triggered lightning program after a ten-year hiatus. During that summer, we became aware of the multiple challenges we would face when triggering lightning. One of the challenges was the identification of thunderstorms suitable to rocket-triggered lightning. This project aims to gather information on clouds forming over Magdalena ridge in order to establish a baseline for clouds that are good for rocket-triggered lightning. Four 12 MP wide field of view raspberry pi cameras will gather images in 360° to gain information about nearby clouds’ positions, sizes, and directions of movement. Additionally, we measure humidity and temperature using a DHT 22 sensor to determine the weather context of cloud formation. The sensor is attached to an Arduino, which will get the GPS timestamp, temperature, and humidity every minute. This data is sent to the Raspberry Pi, which triggers it to capture images from the cameras. On March 7 2025 the setup was deployed on top of the Workman roof at 23:04:42 UTC, and an hour of trial data was collected for clouds to the North and South of Workman. In the summer of 2025 the setup will be ready to be deployed at Langmuir. The ultimate goal of this project is to develop an algorithm to predict good days for rocket-triggered lightning based on images collected by the cameras and data from the humidity and temperature sensor. 

The Direct Axial Flux High-Resolution Motor (DAFR) is an innovative stepper motor designed to be precise and mostly 3D Printable. Its coils are parallel to the drive axle, and the rotor features more teeth than the driver coils, creating a magnetic mechanical advantage. The motor features a ~0.64° resolution, with the ability to half-step for a resolution of ~0.32°. The DAFR is planned to drive WIKEE telescopes and is designed and currently undergoing testing. Once testing is completed, the motor will be enlarged to accommodate extensive payloads that require high resolutions. 

This study explores an alternative method for producing the medical radioisotope Gallium-68 through the process of kinematic recoil induced by bremsstrahlung photons generated from a linear electron accelerator. Kinematic recoil is a photonuclear phenomenon in which an energetic gamma photon is absorbed by a nucleus, produced via bremsstrahlung radiation from a converter, causing the nucleus to enter an excited state. To stabilize, the nucleus emits a neutron, resulting in a recoil of the newly formed atom. This recoiled nucleus can be ejected from its host material and captured in a surrounding medium, such as an aluminum catcher foil. In this work, Gallium-69 targets are irradiated to induce the gamma-neutron (γ,n) reactions necessary for the production of Gallium-68, a positron-emitting isotope used widely in PET imaging and radiopharmaceutical labeling. The feasibility of this approach is modeled using both Monte Carlo simulations and engineering base software, FLUKA and SRIM, to predict recoil ranges, escape fractions, and catcher efficiencies. This method presents a promising alternative to traditional reactor-based and generator-based Gallium-68 production, offering advantages in safety, cost-efficiency, and waste reduction. The results could pave the way for more scalable, accelerator-based production of Gallium-68 to meet growing clinical demand. This work was supported by the U.S. Department of Energy grant number DE-SC00223665. 

The Bosque del Apache Wildlife Refuge in New Mexico faces increasing challenges due to water scarcity and fluctuating water quality, which affect both wildlife and supplemental grain farming. The goal of this project is to support the long-term health and resilience of the refuge by addressing critical knowledge gaps related to water quality. Specifically, the project examines concentrations of major and trace elements, as well as nutrient levels, in both surface and groundwater, and assesses how these relate to agricultural practices and wildlife needs. To capture essential data for effective resource management, the project includes ongoing temporal water quality monitoring. This effort is supported in part by newly installed conductivity data loggers, which provide valuable insights into seasonal salinity fluctuations—information that is crucial for proactive and adaptive management strategies. Ultimately, this research aims to strengthen the long-term sustainability of the Bosque del Apache Wildlife Refuge. 

Traumatic Brain Injuries (TBIs) pose significant health risks in both military and civilian populations due to repeated exposure to blasts and blunt impacts. These injuries remain under investigation because accessing the human head during a TBI is challenging. Polyacrylamide (PAA) hydrogels have been used to replicate brain tissue, however, PAA hinders cell growth. A potential solution involves adding a protein layer to these hydrogels, which may enhance cellular or organoid attachment and improve studies of organoid deformation—a strain measure of damage post-impact. The current approach utilizes Matrigel®, a protein mixture derived from mouse tumors, which can be applied to improve cell attachment. Alternatively, a decellularized extracellular matrix (dECM) can be utilized as a protein-rich layer on the hydrogel surface providing cells with a conducive environment for growth. The dECM can be isolated through cell lysis, a process that breaks down cell membranes and releases intracellular proteins; through methods such as osmosis, and freeze-thaw cycles. Cell surface area analysis indicated no statistical difference between untreated hydrogels, 16.77% ±24.11% (n=4), and hydrogels treated with diluted matrigel, 20.89% ±18.96% (n=6). The findings suggest adding Matrigel to PAA hydrogels doesn’t significantly change its proficiency. However, the dECM analysis revealed statistical differences using the freeze thaw method, 6.69% ±3.1% (n=4), and none using the osmosis method, 7.62% ±5.6% (n=4). Future research will explore dECM methods to further enhance the integration of hydrogels and cells, aiming to create biologically compatible surfaces for TBI research. 

Joint low flow events across multiple watersheds can have far reaching consequences for agriculture, environment, and human communities. However, predicting the spatial joint occurrence of low streamflow remains a challenging task due to the number of factors affecting streamflow, ranging from meteorology to watershed characteristics. This study investigates the spatial correlation patterns of hydrological drought across a large number of instrumented watersheds across the Conterminous United States, with a focus on developing predictive models for joint drought probabilities. We base our analysis on a large dataset (Gages-2) which includes historical streamflow observations, climatic variables, and basin physical characteristics. At each site, we stochastically simulate long streamflow time series data by randomizing the phase of observed streamflow in the wavelet domain. By means of this approach, we preserve spatial and temporal correlation of observed streamflow and at the same time obtain long simulations from which we infer the joint probability of crossing low-flow thresholds across station pairs To further predict spatial low flow occurrence across watersheds, we propose a predictive Machine learning model by comparing the predictive capability of tree based models (XGBoost and Random Forest) with a base Multiple Linear Regression model. This model can be used to predict the joint probability of drought events, learning from both climatic variables and basin characteristics as predictors. Our preliminary results suggest that a technique based on XGBoost is the most robust approach to solve this spatial prediction problem. 

Fibrodysplasia Ossificans Progressiva (FOP) is a rare genetic disease characterized by the gradual ossification of soft tissues within the body. The average life expectancy is around 56, with most being wheelchair-bound by the age of 30. Some of the causes for FOP flare-ups include surgery, injections, and inflammation, making potential treatment options limited. Corticosteroids, preventative management, and Palovarotene are the only treatment options currently available. Modulating the overactive signaling could lead to effective treatment, with the most promising therapeutic target being the activin receptor, ACVRI/ALK2, which has key activating mutations. Synthetic retinoid agonists selective towards retinoic acid receptors, RARa and RARy, can inhibit the excessive formation of cartilage and bone. In 2023, the U.S. F.D.A. approved the use of the retinoid palovarotene, which targets the Gamma receptors (RARy). Similar to palovarotene, Tazarotene is a synthetic third generation retinoid (alongside adapalene) selected for RARy and RARb receptors and is typically used for psoriasis, acne, inflammation, and deep tissue injury healing. A poly (lactic-co-glycolic acid) (PLGA) nanoparticle carrier loaded with tazarotene has been studied for potentially reducing inflammation in the skin and for deep tissue injury healing. Both of these formulations could potentially be used for FOP treatment in the place of corticosteroids, as they could potentially decrease side effects while increasing the anti-inflammatory benefits.