In this study, we propose a highly flexible strain sensor for sensing in-plane strains on a human body surface. Mechano-luminescence-optoelectronic strip (MLOS) is designed with a single sensor node along the strip. MLOS is composed two functional constituents to exhibit two-step mechanical-radiant-electrical (MRE) energy conversion to output direct current (DC) by harvesting mechanical energy. Mechano-luminescent (ML) zinc sulfide (ZnS)-embedded polydimethylsiloxane (PDMS) composites emit light in response to external mechanical stimuli. Mechano-optoelectronic (MO) poly(3-hexlthiophene) (P3HT)-based thin film produces DC, which varies with strain, using the ML light. First, MLOS prototypes are fabricated by depositing MO thin films on the ML composites using a spin-coating. Second, the DC-based strain sensing is characterized by measuring DC when prototypes are subjected to various types of loadings. Lastly, a single node MLOS will be used to map in-plane strain along a surface of the human body experiencing dynamic stimuli. 

When tragedy strikes, the first people on the site of the incident are called First Responders, and among the First Responders is a subgroup known for quick medical assessment and treatment, the Emergency Medical Technicians (EMTs). In emergencies, it is essential to monitor someone’s vital biometrics so that a medical professional may more quickly make an effective diagnosis. This project’s main purpose is to collect patient biometrics to assist EMT decisions. To do this, three sensor systems were designed using photoplethysmography (PPG), thermal imaging, and near-infrared spectroscopy (NIRS) to determine a person's biometrics non-invasively. 

Biomimicry imitates natural systems for applications in engineering and technology, leveraging existing biological solutions to address challenges. Current wildlife monitoring systems utilize methods such as human or drone observation which disturb wildlife, hindering accurate observations of target species. By exploring the integration of robotics and taxidermy, this project aims to bridge the gap between modern surveillance methods and ecology to develop a non-intrusive wildlife surveillance system. The remote-controlled robot designed by our group mimics lizard biomechanics and adhesion techniques, aiming to cause minimal disturbance by reducing cryptic responses to perceived predators. We utilized a taxidermy lizard to create a novel lizard-bot capable of navigating lateral and vertical landscapes while maintaining an anatomically correct lizard exterior. This was accomplished by creating a semi-flexible robotic lizard skeleton consisting of five servo-driven joints with four nano-tape adhesion points. Future applications of this technology include aiding researchers in understanding the complex social behaviors, predator-prey interactions and habitat utilization of wildlife; contributing to more effective wildlife conservation efforts as well as ecological studies within the field of biology. 

From observations using a methane sensor mounted on the roof of Workman Center on NMT campus, there emerge clear patterns in methane concentration throughout the day. In particular, there appears to be generally higher concentration throughout the evening and night, and a lower concentration in the early afternoon. Methane (CH4) is a greenhouse gas most prominently found near the surface in our atmosphere. It makes up 0.00018% of the Earth’s atmosphere and is well mixed. The purpose of this project is to better understand the emission of methane from a variety of sources, including academic sources. It is possible that the measured distribution of methane might be from nocturnal sources or from local accumulation as a result of atmospheric dynamics. In order to understand these emission sources, methane observations over time in conjunction with other atmospheric data, such as wind, temperature, and other trace gas concentration data will be used to determine the properties of the local atmosphere during times of high and low methane to identify patterns and potential sources. The results of this investigation will be presented during the symposium. 

Polyethylene terephthalate (PET) is a plastic widely used for many packaging applications, but has led to environmental concerns due to the single-use nature of the material. PET creation and use leads to plastic pollution, microplastic generation, and plastic accumulation in landfills. Most consumers either do not take the time to properly recycle a plastic product or throw their plastic out if there is mold or bacteria on it. This issue can be prevented by repurposing the plastic waste and extending the lifespan of a product’s usefulness. To do this, recycled PET can be coated in polydopamine (PDA) and combined with tannic acid (TA) to produce an antibacterial plastic that can be reused for consumers and last longer to the consumer than other plastics. PDA is often used as an antimicrobial coating that inhibits cell growth on its surface. TA is a natural compound historically used for its medicinal properties. TA dehydrates bacterial cells and prevents biofilm formation by preventing adhesion of bacteria cell walls to surfaces. Incorporating PDA and TA results in a 97% antibacterial efficacy against S. aureus without changing the chemical or physical properties of the PET. PET combined with PDA and TA can lead to more plastic recycling and reuse, less plastic needing to be created, and provide the consumer with a better packaging product. 

The research presented in this paper was conducted at the Langmuir Laboratory for Atmospheric Research atop Baldy Mountain as a part of the New Mexico Tech GeoScience Program. In previous years (2022 and 2023), research students were introduced to the study of meteorology, climatology, monsoonal flows, atmospheric physics and environmental science. Utilizing scientific equipment and instruments including balloons, radiosondes, kites fielding kestrel and pocketlab electronic systems, measurement of atmospheric constituents from surface and into the stratosphere were recorded. Scientific experiments were conducted to understand the interrelationship between atmospheric conditions and how that relates to the monsoonal flow and its effects on the high-altitude mountain forest biome. Along the course of our study efforts, a research question developed. What is the environment within cloud systems? To investigate this research question, it was decided to launch three weather balloons with attached radiosondes into a cumulus, a towering cumulus, and a cumulonimbus cloud systems while comparing the various constituents. Continuous in-cloud data was obtained and downloaded to the iMet ground station. Various environmental differences were noted. Of particular interest, it was observed that as the balloon penetrated the cloud mass, 80% humidity was recorded. An interesting bump in pressure occurs in Cumulus and Cumulonimbus clouds when traveling from 90% humidity to 100% humidity and back to 90% humidity. This “bump” is missing in the Towering Cumulus.

Digital twin technology is an innovative approach that enables real-time data analysis, simulation and predictions by creating a virtual copy of physical systems. This technology is used in many areas such as optimizing industrial processes, reducing maintenance costs and improving operational decision-making processes. In the mining sector, digital twins are of great importance, especially in terms of monitoring harsh environmental conditions and increasing safety. In this study, a real-time digital twin of the mine site is created using data obtained from various sensors such as humidity, oxygen level, temperature, CO2 and dust concentration. The collected data is visualized on a digital map and provides meaningful information to operators. In addition, using machine learning (ML) techniques, sensor data is analyzed, future processes are predicted, and possible risks can be detected in advance. This approach ensures continuous monitoring of environmental conditions in mines, contributes to the prevention of accidents and the optimization of resource use. Digital twin technology allows mining operations to become safer, more efficient and sustainable. This study highlights the integration of sensor-based data collection, visualization and predictive analysis, revealing the potential of digital transformation in the mining sector. 

Virtual Reality (VR) and Augmented Reality (AR) are transforming robotic control interfaces by providing more intuitive, immersive, and efficient ways for users to interact with robotic systems. Traditional control methods, such as joysticks and pre-programmed automation, often lack adaptability and real-time feedback. In contrast, VR enables users to engage with robots in a fully simulated 3D environment, allowing for natural motion-based control, enhanced visualization, and improved precision. AR overlays digital information onto the real world, enhancing situational awareness and enabling operators to monitor and adjust robotic functions in real time. These advanced interfaces have significant applications in industrial automation, medical robotics, and hazardous environment operations. In industrial settings, AR-assisted robotic control can optimize assembly lines by providing workers with real-time guidance and spatial mapping. In medicine, VR-based surgical robotics offer surgeons an immersive and precise way to perform remote or minimally invasive procedures. AR and VR are also essential for teleoperation in disaster response, space exploration, and deep-sea missions, where direct human intervention is limited or impossible. Despite their potential, challenges such as system latency, hardware constraints, and user fatigue must be addressed to ensure seamless and practical adoption. Improvements in haptic feedback, motion tracking, and real-time data processing are critical to overcoming these limitations. As VR and AR technologies continue to evolve, their integration into robotic systems will enhance efficiency, safety, and accessibility, paving the way for more advanced and collaborative human-robot interactions 

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. 

A key area of space exploration and research is the search for extraterrestrial life in space. Humanity has and continues to send numerous probes to collect samples, images, and data with the eventual goal of eventually visiting these planets for further research. This task raises the significant issue of contamination since anything made on Earth has some form of human contamination. Without proper protocols, we risk discovering signs of life that may actually originate from our own presence, such as hair or skin cells. This research specifically targets the human contamination concern by generating an experimentally verified model to understand and eventually mitigate concerns during space exploration for both humans and probes.  As an individual moves through a quiescent gaseous environment, they generate what is known as a wake, a path of turbulent air that carries a variety of particles. The analogous model developed here compares wake-based contamination to paint particle dispersion from an airbrush. By quantifying the spread of paint particles, the data is scaled to represent the human wake, and tests are aimed at generating a system of equations and a model for understanding this wake in still air. Both large and small scale tests have been conducted to validate the scaling ability of an airbrush jet to an individual’s wake. As work progresses, ongoing testing under different variables allows us to account for and mitigate its impact during space mission 

Swarming, a natural phenomenon observed in birds, insects and fish, follows three key principles: separation, velocity matching, and cohesion. These principles can be adapted to drone technology, enabling coordinated movement within a swarm. While multi-rotor drones have dominated swarm applications, there is significant potential for fixed-wing drone swarms, particularly in search and rescue, delivery, surveillance, mapping, and exploration.

This research proposes the use of the RP2040 microcontroller as a cost-effective flight controller for fixed-wing drone swarming. The RP2040, a dual-core ARM Cortex-M0+ chip running at 133MHz, offers high processing power, multiple I/O interfaces, and efficient task distribution. It connects with sensors such as inertial measurement units (IMUs), GPS modules, airspeed sensors, and voltage monitors, facilitating autonomous flight and swarm coordination.Communication within the swarm and with a ground control system is achieved using the NRF24L01 transceiver. The ground control system, also RP2040-based, provides a human interface via a graphical software panel for issuing commands and monitoring drone vitals.  Fixed-wing drone swarming presents unique challenges, such as maintaining formation while in continuous motion. Improved processing speeds, high-precision GPS, high speed communication and optimized firmware are essential for minimizing latency and ensuring effective coordination. By leveraging low-cost microcontrollers and off-the-shelf sensors, this approach has the potential to revolutionize drone swarm research, development and education, making large-scale swarm applications more accessible and practical. 

Supervisory Control and Data Acquisition (SCADA) systems are essential for the real-time monitoring and control of critical infrastructure, such as water treatment and distribution facilities. However, their reliance on networked sensors and actuators introduces significant cybersecurity risks. A successful cyberattack on SCADA-controlled infrastructure can lead to severe consequences, including service disruptions, equipment failures, environmental damage, and threats to public safety. In this study, we propose a semi-supervised stacking ensemble learning approach for detecting anomalous events in water SCADA systems, including cyberattacks. Traditional supervised learning methods require labeled data for both normal and anomalous events, which can be difficult to obtain in critical infrastructure environments due to the rarity and evolving nature of cyber threats. In contrast, our semi-supervised approach leverages only normal data to train the detection model, making it well-suited for identifying previously unseen or unknown attacks. This capability is crucial for securing water SCADA systems, where emerging cyber threats and operational anomalies may not be represented in historical datasets. The proposed approach employs a meta-learner to strategically combine the predictions of multiple diverse base learners, enhancing both accuracy and robustness. To validate its effectiveness, we conducted extensive evaluations using two real-world water SCADA datasets: the Secure Water Treatment (SWaT) dataset and the Water Distribution (WADI) dataset. Our experimental results demonstrate that the proposed approach significantly outperforms existing semi-supervised anomaly detection algorithms, including the individual base learners within our model. 

The Wide field Infrared Kuiper belt and Exoplanet Explorer (WIKEE) Telescope is a 0.7 meter, folded three-mirror Gregorian telescope that will provide a cost effective method for celestial observation. Instead of having the light be reflected to three different instruments all at once, the system will rotate, connecting to them as needed, providing extra clarity as well as frugality. These instruments so far include two cameras, one being infrared, and a spectrometer. An 80 mm prototype is being constructed which will operate in the 0.7-2.1 micron band. The final 0.7 meter design will have a higher resolution and a maximum field of view of 0.5 degrees. The optical basket of the telescope is a multifaceted mechanism which allows connection to several types of receivers in short succession by means of the “G.W.I.S. Imager”, which rotates the tertiary and fold mirrors on a swivel. Spot diagrams and wavefront analysis present high accuracy and low aberrations. The adapted three mirror Gregorian reflector system is cost effective and versatile, allowing greater operating range with even less aberrations than other refractor designs. The next steps include work on the telescope’s sensors, in particular creating a photodiode interface that will be used for infrared imaging. In the future, an algorithm will be created which will take the image of an asteroid and determine its orbit around the corresponding celestial body. 

Ozone is an abundant chemical in the stratosphere (roughly 15-45 km altitude), formed from photochemical reactions, and primarily serves a purpose of absorbing high-energy ultraviolet light before it reaches Earth’s surface. In the troposphere (from the surface up to the stratosphere), ozone plays a more complex role as both a pollutant and a powerful greenhouse gas. One source of ozone in the upper troposphere is downward transport from the ozone-rich stratosphere, a process which is generally not well understood. In this project, we examine and compare reanalysis data from the MERRA-2 Stratospheric Composition Reanalysis of Aura Microwave Limb Sounder (M2-SCREAM), with satellite measurements from the NASA Ozone Mapping and Profiling Suite (OMPS), in order to utilize these datasets to locate indicators of the exchange of air between the stratosphere and the troposphere. We present 14-day zonal average comparisons of M2-SCREAM reanalysis ozone with measured OMPS profiles. We find that, when comparing a 14-day average between these two datasets, the two profiles tend to agree well. This agreement allows the use of M2-SCREAM reanalysis as an average profile for comparisons with OMPS data in order to identify anomalous ozone profiles. Additionally, we can then examine the meteorological conditions in the M2-SCREAM data that may be associated with the exchange of air between the stratosphere and troposphere and lead to the observed ozone anomalies. Both of these components may be useful indicators in identifying a stratosphere-troposphere exchange event. 

Quantitative schlieren is an advanced optical measurement technique that captures full density fields in supersonic flows. This study builds on previous research applicable to conical projectiles to investigate explosively driven shocks and overlapping axisymmetric shock waves. High-speed schlieren imaging was used to visualize and analyze shocks caused by open-air detonations. To validate the experimental setup, the results were compared to the theoretical predictions of the Taylor-Maccoll solution for 10° half-angle cone projectiles. A mesh grid has been used to account for lens distortion introduced by the camera lens. This step will ensure the accuracy of the images taken by allowing correction for optical distortions. This verification step is crucial in confirming that the flow is axisymetric. This has also been used to accurately measure the arclength of the blasts for any curvature introduced by the lens. Since the flow is axisymmetric, it can be reconstructed using the two-point Abel inversion method. The findings from this study provide a deeper understanding of shock wave behavior in free-field detonations and contribute to the advancement of quantitative schlieren techniques for high-speed flow analysis. 

Building leakage is a concern for building efficiency as well as the health and safety of occupants. One current method of building leak detection is a blower door which can determine overall leak rates but not locate individual leaks. Accordingly, an efficient method of detecting building leaks which may be sealed is of interest. Background oriented schlieren (BOS) is a refractive imaging technique used to visualize flow fields in transparent fluids of varying density or chemical species. For BOS imaging, the only equipment needed is a camera and a suitable background. The simplicity of BOS setups makes it ideal for portability. Here three different types of BOS background for the application of building leak detection are explored: a printed random background, a random background using an overhead projector, and a laser light source through a dispersion filter to create a random speckle. Here, these techniques require a suitable distance for the ratio of distance between the camera and the background (L) and the distance from the camera to the event (t). This test setup tested six different t/L ratios; being 0.035, 0.1, 0.2, 0.3, 0.4, 0.5, to determine when resolution is lost for a BOS system.

Several radioisotopes of bromine are used in nuclear medicine to image and treat diseases. This includes bromine-76, a positron emitter used for PET scans, and bromine-77, an Auger-electron emitter often used for cancer therapy. The traditional method of production involves an incident proton beam from a cyclotron onto a target of selenium in order to induce a nuclear reaction that produces these specific isotopes. However, cyclotrons can be expensive and their yields are often limited by practical heat considerations, leading to the exploration of alternative pathways for the production of radioisotopes. One alternative pathway uses bremsstrahlung radiation, where gamma rays are created by the braking of electrons colliding with a nucleus when traveling through a material. This research project focuses on the bremsstrahlung-induced photonuclear reactions on natural bromine targets in order to produce both bromine-76 and bromine-77. This production route utilizes the 79Br(𝛄, 2n)77Br and 79Br(𝛄, 3n)76Br reactions, neither of which have had yields or cross sections published previously. Fluktuierende Kaskade (FLUKA), a Monte Carlo simulation code used to model nuclear reactions and generate theoretical yields, modeled the above reactions as a preliminary result to base expectations off of. Following this, potassium bromide targets were prepared and brought to the Idaho Accelerator Center where a bremsstrahlung beam was used to irradiate the targets. Gamma spectroscopy was used to measure the yields shortly after irradiation, and further work will be done to determine the yields and cross sections. This work was supported by the U.S. Department of Energy grant number DE-SC0023665. 

This research investigates the engineering properties of cellular cores fabricated from polyurethane foam, carbon foam, and 3D-printed foams, focusing on their behavior under dry and fluid-saturated conditions. Polyurethane foam is known for its widespread use in shock absorption applications. Carbon foam is a newly used foam in aerospace. And research is being done to see the viability of additive manufacturing cellular cores. This study explores the potential of these materials to function as the foundational core in Fluid-Filled Cellular Composites (FFCCs) for adaptive systems designed to mitigate impact and dynamic loading environments. The objective of this research is to generate consistent and reliable data under controlled conditions, enabling the formulation of constitutive relationships for these cellular cores. These relationships are essential for the design and optimization of FFCCs in aerospace, military, and civil infrastructure applications. To this end, testing methodologies will be adapted to evaluate mechanical properties such as modulus of elasticity, curve fitting coefficients, permeability, and porosity. In addition, the study introduces modifications to conventional testing setups to accommodate the unique challenges posed by fluid saturation, ensuring that the resulting data accurately reflects real-world conditions. The investigation aims to compare the mechanical behavior of traditional polyurethane, hydrophilic, and carbon foams, both in dry states and when saturated with fluids of varying viscosities. The results will provide critical insights into the effects of fluid saturation on energy dissipation and structural stiffness; and important optimization of FFCCs cellular core based on performance of the different foams during testing. 

Hot springs in New Mexico, particularly in the Jemez mountains and Gila National Forest, are popular travel destinations for recreation in the state. We investigated the microbial diversity of example springs from both of those widely visited travel destinations. We sampled soil, water and biofilms from these areas to estimate the microbiota of these ecosystems using 16s marker gene analysis. We will present the identified taxonomic breakdown of the bacteria from our samples as well as comparisons between hot springs of differing pH and temperature. We will also compare the bacterial diversity from soils, water, and biofilms from these hot springs. 

Rising urgent care wait times delay vital checks, straining resources, so a prototype device will automatically collect biometric data during check-in. Testing on our five-member team will ensure functionality, with no identifying data collected or stored. The device will include certain engineering specifications such as drop, shock, water, and dust resistance. The gathering of six specific biometrics will be tested; the measurements of these biometrics will just confirm the functionality of the designed electronics. As Electrical Engineering students, it is important to confirm that the design of the electronics is functioning as expected. 

This research, conducted as part of a NIOSH-supported project, focuses on developing a safety-oriented mine navigation system that integrates machine learning, graph neural networks (GNNs), and a graphical user interface (GUI) to improve emergency response in underground mining environments. The central hypothesis is that combining intelligent pathfinding with real-time sensor data and exposure modeling can outperform traditional static evacuation plans in both speed and safety. The system monitors gas concentrations and temperature via distributed sensors, dynamically generating and displaying two evacuation paths—a primary and an alternative—while accounting for hazardous conditions at each node and interpolating gas levels in between. These paths are evaluated not just by distance, but by physiological risk, using established thresholds for symptom onset and fatal exposure times to carbon monoxide and other gases. Using GNN-based algorithms, the system adapts in real time to changing mine conditions, updating routes and highlighting the safest options based on current data. The intuitive GUI offers clear visualizations, enabling both miners and command center personnel to act quickly and confidently during emergencies. Results show the system’s effectiveness in generating safe, redundant evacuation paths that adapt to environmental dangers while providing critical exposure-time context. This work highlights the potential of advanced AI tools and user-centric design in creating smarter, faster, and more reliable mine safety solutions. 

Uranium (U) contamination commonly results from munitions testing, historical conflicts, industrial processes, and mining. Depleted Uranium (DU), a form of U, is less radioactively harmful than natural U but still has mutagenic and toxic properties. While human health concerns related to DU toxicity are well established, effects of DU contamination on microbial communities essential for nutrient cycling are not, thus hindering potential remediation strategies for affected environments. Soil samples were obtained from the EMRTC legacy munitions testing site to determine the impact of DU on arid ecosystems. Five sample sites, including a control, were designated based on predicted DU concentrations and further measured with ICP-MS. The pH and electrical conductivity of the samples were measured while gravimetric analysis was conducted to determine the loss on ignition of organic carbon. Decomposition rates were observed with litter bag incubations, soil water retention was calculated, gas flux measurements for CO2, CH4, N2O were recorded, and soil NO3-/NH4+/PO43- were quantified using spectrophotometric analysis. These parameters give an overall glimpse into the microbial metabolic activity in DU landscapes. Preliminary results indicate a negative correlation between DU concentrations and levels of general soil nitrate, water, and organic carbon. Our poster will report gas flux data from the duration of the lab experiment and a complete statistical analysis of all data collected. Our conclusions provide valuable insights for plant-microbial-based DU remediation strategies with applications for uranium-contaminated areas in New Mexico.