Stander Symposium: School of Engineering

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Additive Manufacturing of Boron Nitride Composite for Tailorable Thermal Transportation

Israa Eltahir Ali Elfaki

The limited thermal conductivity of many polymers has constrained their widespread use,despite their appeal for their resilience, affordability, and lightweight nature. Hexagonal boronnitride (h-BN), the structure analog of graphite, has many applications due to its superbproperties. Owing to its stacking layer structure, h-BN possesses anisotropic thermaltransportation property, exhibiting superior thermal conductivity along its in-plane direction butlower cross-plane thermal conductivity. Developing h-BN composites with controllable BNalignments will enable great potential for making high thermal conductive components for variousapplications. Digital light processing (DLP) is one of the additive manufacturing (AM) techniquesthat can be used to control h-BN plate orientation in a polymer matrix. This research investigatedthe DLP-printed h-BN composites, and the results showed the controllable alignments of h-BN inthe composites for improved thermal conductivities.
Additive Manufacturing of Nickel-Enhanced SiC-Based Composite Materials

Jinchen Han

This study employs Direct Ink Writing (DIW) 3D printing technology to fabricate ceramic matrix composites (CMCs) with complex geometric structures, enabling the production of components with intricate designs that are challenging to achieve through conventional methods. The incorporation of nickel (Ni) powder as a reinforcement phase enhances the rheological properties of the slurry during the preparation process, ensuring printability and structural integrity. The resulting CMCs exhibit improved mechanical properties, including higher strength and toughness, compared to unreinforced ceramics. These enhancements are likely attributed to the melting of Ni during sintering and its subsequent reaction with silicon carbide (SiC), forming a robust interfacial bonding network. This work aligns with recent advancements in additive manufacturing of CMCs, offering insights into optimizing slurry formulations and sintering mechanisms for high-performance applications.
A Non-volatile Ferro-photonic Memory Device

Asela Perera

Commercially existing photonic integrated memory device architectures implemented with MRRs are volatile, implying that once the bias is removed, the stored memory is erased. While the functionality is excellent for optical data switching and optical data modulation applications, the volatility is unsuitable for optical memory applications where the bias needs to be ON at all times to store the data in the MRR implying a significant static power consumption. Such a feature is unsuitable for photonic computing applications in neural networks where training weights need to be stored for a long time without any active power consumption. An energy-efficient non-volatile memory is one of the missing photonic building blocks for optical computing. Micro ring resonators (MRRs) are integral components of silicon photonic integrated circuits (PICs) that can change amplitude and phase of light. The resonance wavelength of MRRs can be shifted by changing the refractive index of MRR material. A hybrid ferroelectric material needs to be integrated with silicon to store the shift and hence the data, when the actuating voltage is removed. Recently, foundry compatible hafnium-zirconium-oxide (Hf0.5Zr0.5O2, HZO) has been demonstrated as a suitable ferroelectric in memristor applications in electronics. In this work, we present an initial prototype of a non-volatile high-speed ferroelectric optical memory device with HZO integrated on MRRs.
Automated System For Photonic Integrated Circuit Measurement

Daniel Donnelly

In recent years, with the advent of mature miniature semiconductor fabrication processes, the photonic integrated circuit (PIC) has emerged as a potential solution for the increased power consumption and bandwidth of conventional electronic computing technologies. As low-energy, optical devices, PICs serve to bring the solutions and advantages of optical technologies down to the form-factor of typical electronic microchips, including applications in telecommunications, high-speed computing, sensing, and quantum computing. However, despite the existing technologies for semiconductor fabrication, PICs, unlike their electronic counterparts, are exceedingly difficult to package and test, with each part of the process individually taking up roughly 30% of the manufacturing cost. Thus, in recent years, much focus has been placed on reducing these costs through increased automation of the various testing processes, particularly the fiber alignment process, in which, for a given device, the input and output fibers are moved to the optimal position for maximum throughput. The following paper describes the construction and implementation of an automated PIC measurement system in the Silicon Photonics Lab at the University of Dayton, including implementations of automated fiber alignment routines. The system exceeds state of the art output metrics in terms of measurement throughput and includes components for both optical and electric device measurement. The paper also describes the system’s use in measuring an innovative miniature on-chip Fourier Transform spectrometer presented at the SPIE Defense+Commercial Sensing 2023 conference.
Autonomous Vision System for Hazardous Object Detection in Construction Sites

Anurag Mallik

Construction sites pose significant risks to workers due to the presence of various hazardous objects. These items can be sharp or blunt, or even cause electrocution. With the common denominator being that all can lead to serious accidents. During construction, all personnel on site must take proper precautions when handling hazardous objects. While larger items are easily visible, smaller tools like nails, hammers, and drill machines often go unnoticed. If these objects are left unattended in active areas, they can lead to life-threatening incidents in construction zones. In this research work, a computer vision algorithm has been proposed to identify construction tools in a construction zone as part of a larger pipeline for construction hazard detection. Specifically, this work focuses on images of construction zones which have been captured from various angles. The Segment Anything Model (SAM) is used to segment these images allowing them to analyze regions of interest. Regions selected for further processing are done by calculating bounding boxes which are based on the segmented areas. Through experimentation, an optimal size of the bounding boxes to reduce the number of boxes to processes showed bounding boxes that capture an area of 3% to 8% of the total image size are typically relevant to detect a hazardous object in a construction scenario. These resulting bounding box areas in the image are fed to a feature extractor, DINOv2 that returns the object feature matrix to feed into a fully connected three-layer neural network classifier. The classifier identifies an object feature set belonging to one of the twenty predefined hazardous objects if the score of the highest probability output node of the classifier is beyond a predefined threshold value.
Bio-Inspired Rotating Empennage (BIRE) - Desktop Model

Ryan Rotsching

A concept fighter aircraft is being investigated by the Air Force Research Labs that eliminates the vertical tail and uses a bio inspired rotating empennage (BIRE). The motion of the empennage is intended to mimic the agile flight displayed by birds of prey. To assist in communicating the mechanical concept, a desk-top demonstration model was created. Each part in the model is constructed primarily of additively manufactured (AM) components, allowing each component to be custom designed and swiftly manufactured to maximize functionality and accuracy. These components were based on the existing structure of the baseline F-16 and modeled in SolidWorks. The project involved research into different AM techniques and most appropriate process for each component. Two different variants are being constructed: 1) a simple internal structure demonstrating the functions of the BIRE, and 2) a topographically optimized solution. The results of these models allow visualization of the functionality and viability of the BIRE concept.
Bridging the Gap in Industrial Energy Modeling through Lean Energy Analysis

Sean Kapp, Gavin Mchale

HVAC systems account for a significant portion of the energy consumption within the industrial sector. Specifically within chemical manufacturing facilities, fume hoods contribute heavily to HVAC energy use by continuously exhausting conditioned air. While advanced energy modeling techniques exist, small and medium-sized manufacturers (SMMs) often lack the resources and data required to implement complex machine learning-based solutions. An inability to collect useful information on energy patterns throughout the year can be a large obstacle for these facilities in deciding which changes will have the largest benefit for the company. Depending on the complexity of the energy model, predictions can be made based on a variety of factors. Changes in outdoor temperature plays a primary role in the variation of monthly energy usage. This study presents Lean Energy Analysis (LEA) as a practical and effective approach for assessing weather-dependent energy consumption in manufacturing facilities. LEA utilizes energy billing data to model energy-weather dependence through a piecewise linear changepoint analysis, enabling manufacturers to identify inefficiencies and predict energy savings from efficiency measures. A comparative analysis between LEA and the Random Forest (RF) machine learning model was conducted to validate the accuracy and utility of LEA for energy modeling. The results demonstrate that while RF models can provide strong predictive accuracy, they lack transparency and requires many features to be robust. In contrast, LEA effectively identifies independent energy usage, changepoint temperatures, and weather-dependent slopes as distinct, physically meaningful quantities, offering actionable insights for energy optimization without the need for extensive sensor networks. A case study is conducted at a chemical manufacturing facility where excessive fume hood usage was identified as a major contributor to HVAC energy waste. By applying LEA, the research team quantified the energy savings potential of lowering fume hood doors when not in use. Implementing this measure resulted in an annual reduction of 191,259 kWh in electricity and 729 MMBtu in natural gas, leading to cost savings of $18,851 and a carbon footprint reduction of 129 metric tons. This study highlights the advantages of LEA for SMMs seeking to optimize energy efficiency without the cost and complexity of high-tech energy modeling solutions. By leveraging historical data, LEA provides a low-cost, data-driven framework for energy assessment and sustainability improvements in industrial facilities.
Characterizing the Broadband Frequency Response of Pressure-Sensitive Paint

Charles Strunc

Pressure-Sensitive Paint (PSP) is a valuable tool for measuring pressure distributions in aerodynamic testing, but its effectiveness depends on its response time to pressure fluctuations. This research investigates the frequency response of PSP using a custom-built resonance tube designed to generate controlled pressure oscillations across a wide frequency range. The tube exploits the resonant properties of an air column to amplify pressure fluctuations produced by a speaker system, theoretically enabling precise characterization of PSP behavior at frequencies from 100 Hz up to 60 kHz. PSP pressure readings are compared to a high-precision transducer to quantify phase lag and signal attenuation, providing insight into the operational limits of different PSP formulations. The goal of extending frequency response characterization beyond the typical 10 kHz threshold offers a more comprehensive understanding of PSP performance at high frequencies. The resonance tube developed in this work establishes a permanent experimental setup for future PSP testing and optimization, supporting advancements in high-speed aerodynamic pressure measurements.
Clinical Translation of Virtual Reality Motion Capture for Upper Extremity Therapy Using Machine Learning

Skyler Barclay

Virtual reality (VR) has become popular in research due to its ability to present clear and customizable tasks. Infrared (IR) motion capture allows for the collection of full kinematic data, however the cost may not be feasible for most clinics. Vive trackers allow for integrated wearables and VR therapy at a lower cost. Our current VR motion capture system requires segment definitions from the IR motion capture system in order to build an accurate skeletal model. The aim for this study is to output kinematics from the raw VR motion capture data using a Bidirectional Long-Short-Term-Memory (BLSTM) algorithm trained with joint kinematics calculated from the IR motion capture system.IR and VR motion capture of the upper extremity was collected simultaneously, in Nexus and Brekel respectively, while participants played customized levels in Beat Saber. The participants were instructed to slice through the virtual blocks with a saber in the directed position, orientation, and correct arm. To determine if shoulder, elbow, and wrist joint kinematics can be predicted using raw VR motion capture data a person specific BLSTM algorithm (n=3) was trained in Python on IR joint kinematics from the first visit (lookback = 100) and tested on the participants’ second visit data.The BLSTM results found an average error of ±10° for the joints. Collecting known joint angle poses, filtering the input data, and fine tuning the algorithm hyperparameters should decrease the error further. This means one baseline IR capture could make it possible for clinics to predict upper extremity joint kinematics of a patient during these customizable Beat Saber therapy games, and possibly other motions, with only the VR equipment, Brekel, and Python. Additionally, the use of VR therapy allows for individualized and fun therapies with quantitative results to track progress.
Design and Testing of a CubeSat Radiator Prototype

Abigail Boyer

As part of the NASA CubeSat Launch Initiative, this research consists of designing and testing a CubeSat satellite prototype. Primarily used for research purposes, a CubeSat is a cuboidal nanosatellite with side dimensions of 10 centimeters. Due to the harsh space environment, the CubeSat experiences rapid temperature fluctuations, leaving it susceptible to damage. As a result, only about 50% of current CubeSats complete their mission. Unfortunately, the current technology used to modulate temperature on typical spacecraft is too sizeable to be applied to a CubeSat. Therefore, the objective of this research within the NASA CubeSat Launch Initiative is to design an effective system to maintain the operating temperature of the CubeSat radiator. As part of the current CubeSat design, a system of fins, coated with phase change material (PCM), has been created to actuate outwards when heat disperses from inside the radio. The fins are coated with phase change material (PCM). Phase change materials are exceptionally effective for their ability to store thermal energy and will remove heat from the CubeSat when its fins are exposed to the environment. We were able to achieve at least 45 degrees of actuation through the use of nickel-titanium wires. Nickel-titanium is a shape memory alloy, meaning it can be manipulated into any desired shape or form and can revert to its original form when heated. Within the CubeSat application, the heat applied to the nitinol wire drives the PCM-coated fin outward. We developed our plaster molds in the lab and used kilns to train the wires reaching temperatures over 800 degrees Celsius. We were able to test our prototype within a vacuum chamber using electrical feed-throughs, thermocouples, and polyamide heaters to see if our fin would actuate under conditions most similar to those of an actual CubeSat.As verified through laboratory testing, the nitinol wire can be geometrically manipulated and then returned to its original configuration following exposure to heat. Additionally, the nitinol was strong enough to actuate the fins when excessive heat was applied. To conclude, the phase change material opens up endless opportunities for innovation within satellites and spacecraft innovations, supporting the actuation and movement of complex technology without the traditional equipment.
Designing and Manufacturing Solar Dryers for Increased Marketability of Agricultural Products

Daniel O'Connor

In the rural pueblo of Huyro, Peru, many community members have agriculture productsgrowing on their land, but are unable to profit from them due to the large labor requirement anda local surplus of raw product. With the addition of a solar dryer, these community members caneasily increase the marketability and profit of their products. The solar dryer uses the heat of thesun to dehydrate fruits and dry coffee. Dehydrating the fruit allows the farmers to sell theirproduct to city bars and restaurants that use the dehydrated fruit as ornaments on their food andcocktails. From an engineering perspective, we were responsible for mapping out a circuit diagramthat would allow both the inlet and outlet fans to be powered from the same solar panel. Fromthere, we wired the control box and the power systems in the dryer accordingly and installed thesystem. The creation of joint pieces for Fidel’s dryer required us to fix and test two 3D printers.Lastly, the dryer needed a door. This presented the challenge of putting a rectangular door on atriangular dome. Through much engineering trial and error, we were able to create a functionaldoor that was continuous with the exterior of the dome to ensure proper functionality.
Design of a Pipe Inspection and Remediation Soft Robot

Simon Baker, Daniel Gubser, Adomas Mazeika

Soft robotics is a rapidly evolving field that is advancing the development of surgical devices, prosthetics, and robotic gripper systems. In this work, we explore the design of a soft robot capable of crawling along pipes for inspection and remediation purposes. A common challenge in the rehabilitation of older buildings is the inspection and clearing of existing sewer lines for potential reuse. Frequently, blockages prevent these pipes from being returned to service. When such obstructions are present, the typical solution often involves demolition and reconstruction of floors, walls, and plumbing. A device that could navigate old pipes—capable of turning corners, adjusting to varying diameters, and performing tasks within the pipe—would be extremely valuable. This work presents the modeling, rapid prototyping, assembly, and testing of several key components of the pipe-crawling soft robotic system.
Design of GeSn single photon avalanche photodiodes for short wave infrared detection

Alexander Skender

There is a desire for single photon avalanche diodes (SPADs) capable of detecting light in the SWIR wavelengthrange for Lidar systems to increase their range while maintaining eye safety. It is also desirable for these SPADsto be CMOS compatible. Ge-on-Si SPADs have been demonstrated by several groups, but Ge only extends thewavelength response to around 1.6 µm. This paper investigates the design of SPADs using GeSn as an absorberto increase the wavelength response to 2 µm. We will compare the use of Si and Ge as a material for themultiplication region.
Design Space Exploration for a Novel Self-Healing Elastomer, Informed by Bayesian Optimization

Robert Drexler

Self-healing elastomers are an emerging class of materials capable of mitigating vulnerability to externally-induced damage. Recent advancements in polymer chemistry have led to self-healing elastomers that are 3D-printable, exhibit real-time self-healing in the absence of external stimuli (e.g., heat, light), and use commercially available (COTS) precursors to enable production at scale. However, at present, the trade-offs between virgin mechanical properties and self-healing efficiency are not well known. To address this research opportunity, this talk presents an experimental program – informed by a Bayesian optimization platform – to (a) facilitate design space exploration and (b) investigate the interplay between virgin mechanical properties (i.e., hardness and toughness) and self-healing efficiency (e.g., ratio of healed toughness to virgin toughness) as chemical composition is varied. The material of interest is BeckOHflex, a new acrylate/thiol-ene elastomer that exhibits real-time, autonomous self-healing and is exclusively prepared from COTS precursors. The experimental design was conducted by varying the crosslinker and thiol components from 0-10% by volume while holding the molar ratio of acrylate and photoinitiator constant. Test samples were cast in custom silicone molds and cured using an external UV lamp. Hardness data was obtained using an analog Shore OO durometer, and mechanical property data was collected through uniaxial tension testing. Informed by previous-iteration experimental inputs (chemical composition) and the resulting outputs from mechanical testing (virgin hardness, virgin toughness, and self-healing efficiency), a Bayesian optimization platform (EBDO+) was used to suggest next-iteration experimental inputs. Through this iterative process of synthesizing, testing, and analyzing different compositions throughout the experimental campaign, a well-defined Pareto frontier will be determined to bound the design space, allowing for a fundamental, quantitative understanding of tradeoffs between virgin mechanical properties and self-healing efficiency. It is expected that the Pareto frontier will be determined after tens of experiments out of a possible 2,000+ discrete input parameter combinations.
Development and Validation of General Greenhouse Model for the University of Dayton

Jacob Brenner

The use of a greenhouse model is essential to ensuring that any greenhouse design presents the best value that is possible within that region of the world. Often times, greenhouse models within research papers are created, with varying levels of detail, but the models themselves are often not shared openly. This problem can be solved via some of the greenhouse models that have been made openly available, but unfortunately, the vast majority of these require a subscription, either to the model itself, or to a software that the model was built on. Thus, the purpose of this paper is to create a clear open source model, created in the programming language Python, that is published alongside this paper. This model was validated through data collected for a short period from late August to early October of 2024 within two greenhouses in the area of Dayton, Ohio. The data was collected via temperature and humidity loggers placed within 3D printed solar shields that were previously validated, while the two greenhouses contained two different environments, one with vegetation and no electronic equipment, and one with no vegetation and a fan present.
Development of a novel atmospheric chloride detector

Hannah Buchanan

Silver is often used as an indicator in atmospheric corrosion studies to better understand the effect of environmental chemistry on corrosion severity. A common experimental method involves the exposure of silver coupons at environments of interest, allowing corrosion products to form, followed by coulometric reduction analysis. However, this type of analysis makes a key and often overlooked assumption: that the composition of the corrosion film does not change after initial formation. This assumption of chemical stability of the corrosion product has not been extensively studied and does not account for possible chemical changes within the corrosion products due to ongoing environmental exposure or storage conditions.In the first phase of the study, coulometric reduction and X-ray photoelectron spectroscopy (XPS) were used to study multi-component lab-grown silver corrosion product films, which reveled differences in the corrosion product films based on component deposition order. This was inferred to be due to a substitution reaction within the corrosion product film which occurred during exposure to other electrolytes during the deposition of the subsequent films.In the second phase, salt spray was used to demonstrate that the amount of substitution reaction that occurs from Ag2O to AgCl is proportional to the extent of exposure to NaCl. Ag2O films were electrochemically grown and exposed to salt spray under varied conditions. This demonstrates the applicability of silver oxide films for the quantitative detection of atmospheric chloride deposition in a new way.
Dynamic Radiator Fins for CubeSat Cooling

Anthony Lococo

This project aims to develop and optimize a dynamic radiator fin to cool any electronic device in a space environment. Historically, these devices have been subject to temperature limits, as they cannot become too hot or too cold within their orbital duty cycle. This duty cycle corresponds to a spacecraft's orbit, as the device needs to idle or perform functions along certain arcs during its orbit. Traditionally, managing this has been done through creating a conduction pathway to space directly from the electronics, or through constructing static radiators which protrude into space. Both of these issues are problematic, as they cannot adapt to the variable heat loads which the electronics induce. The solution is a dynamic radiator, which is able to retreat inside the spacecraft and protrude outward according to the demands of the system. When inside, it will collect the heat of the system, and when outside, it will release it into space. The device will be passively actuated via nitinol, which has shape-memory alloy (SMA) characteristics. As the nitinol undergoes its phase change, it either heats up and stiffens to a trained shape or cools down and subsequently relaxes. This will be implemented by instituting nitinol wires to bend outward, springs to extend, or torque tubes to twist, forcing the radiator fin to extend outwards into space. The design consists of material characterization, experimental testing, and theoretical modeling of the system. Experimental testing includes identifying an optimal actuation nitinol attachment method. The Thermal Desktop model will be used to tune contact resistances. The Python model will vary properties significant to heat transfer to optimize the design. Current results show that proper thermal management can be achieved via modeling, and experimental testing has shown a maximum actuation angle of 60 degrees, which provides significant heat transfer into space.
Electrical reversible switching of Phase change materials

Osama Rana

Phase change materials (PCMs) undergo a reversible solid-state transition between amorphous and crystalline states upon heating by applying electrical or optical pulses. While crystallization can be induced by heating on a hot plate, amorphization requires heating above the melting point followed by rapid quenching. This study presents the design and fabrication of a microdevice enabling reversible switching through electrical pulses. GST pixels are deposited on a thin film metal strip to facilitate phase transitions. Electrical current will pass through metal thin film strip ,which will heat pixel via joule heating. To optimize device performance, we conducted resistivity measurements to select a suitable heater material and determined the optimal heater thickness for efficient impedance matching between the electrical pulse source and the device.
Empowering Innovation: Trailblazers in STEM

Vishal Ayyappan Pillai, Piyush Dugge, Sathwik Juvvadi, Jahnavi Kurapati, Shivani Mantoo, Dhana Lakshmi Pilli, Ashwini Rathnapuram, Rohan Rajpal Raut, Hardik Maheshbhai Solanki, Lilly Tiriveedhi

The fields of Science, Technology, Engineering, and Mathematics (STEM) have historically been shaped by groundbreaking innovations and pioneering minds. However, despite their invaluable contributions, women in STEM continue to face systemic challenges, including gender bias, underrepresentation, and limited access to leadership roles. This symposium aims to highlight the achievements of trailblazing women in STEM, the barriers they have overcome, and the transformative impact of diversity in driving innovation and progress.Our discussion will delve into the historical milestones set by women in STEM, from early scientific pioneers to contemporary leaders who are reshaping the industry. By examining key success stories, we will identify the common challenges faced by women in these domains, such as societal stereotypes, the gender pay gap, and the lack of representation in leadership positions. Furthermore, we will explore strategic initiatives—including mentorship programs, policy reforms, and corporate inclusivity efforts—that have been instrumental in fostering a more diverse and equitable STEM ecosystem.A critical component of this session will be an analysis of how organizations can actively support and empower women in STEM. We will present data-driven insights on the business case for gender diversity, showcasing how inclusive workplaces lead to greater innovation, enhanced problem-solving, and improved organizational performance. Additionally, we will discuss actionable recommendations for companies, academic institutions, and policymakers to cultivate an environment where women can thrive as leaders, innovators, and changemakers.By shedding light on the stories of trailblazing women and the ongoing efforts to bridge the gender gap, this symposium aims to inspire a collective commitment to breaking barriers and building a future where talent and ambition, regardless of gender, are fully recognized and nurtured.
Engineered Inter-Flake Interactions for Continuous MXene Films

Kennedy Brown

MXenes are an emerging class ultra-thin materials (<5 molecular>layers), also known as two-dimensional or 2D materials, that have garnered significant interest across various research domains due to their exceptional physical properties, including high conductivity (> 8 kS cm-1), electromagnetic interference (EMI) shielding (>58 kdB cm2 g-1), and tunable hydrophilicity. To tailor these properties, MXene films can be fabricated using a layer-by-layer approach, enabling precise control, enhanced stability, and tunability of the materials system. The method of film development, such as drop casting, interfacial assembly, or spray coating, is critical in this assembly process and has a significant impact on electronic and optical properties.Currently, there is limited research directly comparing the layer-by-layer assembly of different film formation methods for Ti3C2Tx MXene. This study aims to characterize and standardize these methods for future MXene development, including comparisons between MXene flakes and scrolls. Additionally, we demonstrate that dopamine not only binds effectively to our system but also enables adjustment of interlayer spacing, as determined by AFM height measurements, thereby influencing the overall properties of the thin film.
Enhancing Deep Collaboration through Experiential Learning: The Impact of the Stitt Scholars Program

Conor Atkins, Trent Borgmann, Alejandro de Jesus, Brooke Hunstad, Jennifer Jarog, Iga Jaromin, Lucianna Nice, Kevin Nudo, Najwan Orabi, John Protz, Luke Ready, Yadiel Roque

Collaboration in higher education has significantly improved, with programs increasingly incorporating collaborative elements in their curricula. Despite these advances, there is a pressing need to further enhance interdisciplinary collaborations through experiential learning. The Stitt Scholars Program exemplifies this by offering students from the School of Engineering, the College of Arts and Sciences, and the School of Business Administration opportunities to work with startup companies at the HUB, supported by PNC Bank. Students commit ten hours weekly to their projects and engage in lectures on innovation and entrepreneurship. The program's success has attracted further investment, enabling its expansion and continued contribution to interdisciplinary education and community engagement.
Enhancing Quadrotor Autonomy Using Robust Control Algorithms

Kevin Johnston

In the evolving landscape of unmanned aerial vehicles (UAVs), the autonomy and stability of quadrotors are crucial, especially in critical applications such as search and rescue missions and surveillance. This research focuses on the development and implementation of planning and control algorithms within the Robot Operating System (ROS2) framework. Initial work focused on developing Proportional-Integral-Derivative (PID) control algorithm in a realistic simulated environmental conditions, incorporating the effects of sensor noise. Following successful simulations, the study transitioned to real-world testing, validating the effectiveness of the proposed solutions in ROS2. The work conducted has not only demonstrated the practical utility of these algorithms in both simulated and real-world environments but has also laid the groundwork for more advanced applications in aerial robotics. The successful integration of ROS2 has opened up new avenues for modularity and scalability, critical for the ongoing evolution of autonomous drone technology.
Enhancing Quadrotor Autonomy using ROS-based Control Algorithms

Kevin Johnston

In the evolving landscape of unmanned aerial vehicles (UAVs), the autonomy and stability of quadrotors are crucial, especially in critical applications such as search and rescue missions and surveillance. This research focuses on the development and implementation of planning and control algorithms within the Robot Operating System (ROS2) framework. Initial work focused on developing Proportional-Integral-Derivative (PID) control algorithms in realistic simulated environmental conditions, incorporating the effects of sensor noise. Following successful simulations, the study transitioned to real-world testing, validating the effectiveness of the proposed solutions in ROS2. The work conducted has not only demonstrated the practical utility of these algorithms in both simulated and real-world environments but has also laid the groundwork for more advanced applications in aerial robotics. The successful integration of ROS2 has opened up new avenues for modularity and scalability, critical for the ongoing evolution of autonomous drone technology.
Enhancing Student Engagement and Learning: Adapting Teaching Strategies in an Undergraduate Data Analytics and Programming Course

Shivani Mantoo

Effective undergraduate teaching is centered on creating an engaging, supportive, and inclusive environment that fosters student growth and learning. As the first master’s student to serve as an instructor of record in the Engineering Management, Systems, and Technology Department, the challenges of teaching were approached with enthusiasm, adaptability, and a student-centered philosophy.While teaching SET 153L (Introduction to Data Analytics and Programming) for the first time in Spring 2024, it became evident that many students struggled with the flipped classroom model, particularly in transitioning from self-paced learning to active. In response, the teaching approach was restructured by initiating each session with a guided class activity and hands-on learning, allowing students to build confidence and solidify foundational concepts before advancing to more complex problem-solving tasks. This adjustment resulted in significant improvements in both student engagement and comprehension, fostering a more interactive and supportive learning environment.In addition to curricular modifications, an intentional effort was made to cultivate an inclusive and supportive classroom culture. Recognizing that some students were hesitant to ask questions, open dialogue was encouraged, consistent opportunities for one-on-one meetings were provided, and a space was created where all students felt comfortable seeking help. These efforts reinforced the belief that effective teaching transcends content delivery—it involves creating an environment in which students feel empowered to engage and grow.The positive impact of these adjustments was reflected in student feedback, which was both rewarding and motivating. The opportunity to teach the course again further strengthened the commitment to continuous improvement, both in refining teaching methods and enhancing student engagement.This teaching experience has been transformative, with ongoing efforts to evolve the approach, learn from students, and contribute to an enriching educational experience.
Ethos Research and Development: Solar Thermal Adsorptive Refrigeration (STAR)

Brendan Alexander, Ty Rapp, Clayton Rosso, Molly Savage

The Solar Thermal Adsorptive Refrigerator (STAR) project in partnership with the Ethos R&D program at the University of Dayton seeks to reduce the need for reliable refrigeration in developing communities. The STAR refrigerator does not require electricity for operation and uses a safe, environmentally benign, and locally available adsorption pair of activated carbon and ethanol. This project explores the effect of different activated carbon pre-treatment methods on the cyclic performance of the STAR system.