Project Goal/Summary: The purpose of this project is to develop an improved, more advanced, patient friendly urinary drainage catheter. The proposed device will reduce pain, prevent inflammation and limit and prevent infection, all of which are major advances overcoming the limitations of current designs. Successful development of this device will be a step forward to broadly reducing medical morbidity and mortality.

Requirements: Step one: Teams will research the limitations of current Foley catheter systems as to pain, inflammation and infection. Step 2: A series of strategies and designs will be developed for local controlled release of analgesic, anti-inflammatory and anti-infective agents (specific easily obtainable drugs will be used). Controlled release formulations using drug delivery polymers will be configured and release kinetics will be modeled and tested in vitro. Step 3: In parallel an “electroceutical” strategy will also be pursued to incorporate into the catheter, i.e. local electromagnetic fields or ultrasound, as a synergistic means of reducing infection on the catheter. Step 4: Mock catheter constructs will be made and tested in an in vitro tissue/infection model and the best design will be advanced. Step 5: A temperature sensor element will be incorporated in the catheter to measure subtle temperature rise associated with inflammation and infection. Step 6: A GUI/Cell phone readout and data tracking system will monitor, report and telemeter infection potential to the cloud or EHR. Step 7: A parallel customer survey will be conducted on features to evaluate market acceptance and help provide feedback for design improvements.

Friday afternoon mentoring sessions (for all Kidney/ACABI teams) on a rotating pre-scheduled basis will be in place to provide adequate guidance.

Skills Necessary: Biomedical Engineering, Mechanical Engineering, Electrical Engineering Computer Programming, Machine Learning. Knowledge of sensors, materials and polymers, coding.

The 3D ultrasound foot scanner consists of a testing platform, a servomotor actuator, a microprocessor controller, and software to collect and process ultrasound imaging and stiffness data collected from the arch of the foot. In this second phase of the project, the team will make several improvements to the mechanical structure of the platform, the data acquisition software, the data processing software, and the graphical interface.

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Design of a conveyance system utilized in the recycling/reuse of HP PA12GB powder. The system should be able to attach to the top of a 55gal holding drum, and be movable with two person carry, between barrels. The system should be a closed loop, in order to avoid contaminating the work environment. The system should be able to draw the powder from the barrel, whether full or near empty, and convey it up to the chambers above. The first of these chambers needs to be able to perform a mixing, to proper ratio, of colorant and other additives. The second chamber should be a hopper that can feed an extrusion machine, and is able to keep a measured amount of mixed material on hand for the extruder, without allowing starvation. A bonus for this project would be one of two paths: 1. retro-fit the current extruder to gain more consistent filament diameter; or, 2. create a better extruder.

Project Description:
Design, build, and bench test an optical metrology module that measures the size, velocity, and particle trajectory of microspheres with diameters <500um.
Background:
ASML in Rancho Bernardo, CA develops EUV (Extreme Ultra Violet, 13.6 nm radiation) lithography light sources for EUV lithography tools using LPP (Laser Produced Plasma) technology. EUV generation takes place inside a large diameter (>1.5 m) chamber by vaporizing/ionizing small liquid Sn (Tin) droplets at high repetition rates (50 kHz) using a powerful CO2 laser. The vaporized/ionized Sn droplets produce EUV radiation which is collected by a mirror and focused into a lithographic scanner. The scanning system exposes lithographic patterns on semiconductor wafers using the EUV light.
During EUV source operation, the Sn droplet stream passes through a light curtain (for example, a light curtain produced by a laser beam). The reflected light from the curtain is collected by a solid state detector whose signal is used to fire a powerful CO2 laser at the “proper time” to vaporize/ionize each Sn particle in the stream – thus producing EUV light.
Problem and Capstone Statement (using microspheres):
The detection of Sn particles and their position in space at a given time is critical to the operation of the LPP EUV source system. It is desirable to produce a metrology system that measures the size, velocity, and trajectory of moving particles – microspheres.
The project task is to design and build a prototype system using commercial off-the-shelf parts, supplemented by 3D-printed or locally-machined parts, to deliver a unit that will be tested on a U of A test bench. The approximate size of the system (metrology unit) consisting of the microsphere launch system, light source, and detector should fit inside a cube of no more than 3ft on each side – additional circuitry for collecting and displaying outputs need not be included in the contained metrology unit. Further details will be explored by the team during conversations with ASML leads.

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Project Background/Scope: The role of the health care encounter – whether on the medical office, clinic, hospital, home or field is critical in obtaining relevant information to guide and direct the delivery and accuracy of care. Studies have shown that > 70% of diagnoses and advancement of care stems from the physician or health worker carefully questioning and observing the patient. Sadly, patient encounters today have become shorter as to time spent, with the physician hampered while performing an exam by the burden of electronic health record (EHR) data entry and use of a computer. Studies have also shown that many correct diagnoses are made by the doctor using information, such as: what and in what way the patient speaks, how the patient looks and acts, how the patient behaves, how the patient sits, how the patient walks, and other information gained by focused, attentive, one–on–one patient encounters and consultations. In routine doctor-patient interactions today much of this information is not being recorded and is lost.

This project will develop tools to be used in a “Smart Patient Exam Room” to capture information that the physician often misses, AS WELL AS DEVELOP TOOLS THAT GO BEYOND – TO EXTRACT NEW INFORMATION – creating VERBAL AND DIGITAL BIOMARKERS OF DISEASE. This project benefits from and builds upon work done by two previous Sr. Design teams who built a basic system to capture sound and image; and from a dedicated room in COM-T for this purpose allocated to this project by the medical school!

Requirements: I. Hardware – re-up a kit for sound and visual capture – can benefit from prior Sr Design team – kit should be portable (for use in any space) and fixed (for use in dedicated exam room in med school), including high fidelity microphones and cameras. II. Software/Computational Tools/AI. The team will build three sets of tools:
1. Voice to text Symptom Frequency Index and related Common/Keyword/other word Index Analysis Tools. Step one: Develop a dictionary of diagnostic terms from the medical “review of systems” (symptoms and signs) and from short recordings of patients with specific diseases, e.g., a patient with dyspnea might say, "I have been having a hard time catching my breath recently. I can't walk around the grocery store without stopping to catch my breath..." all this forming the analytic lexicon. Step two: Voice to Text and Word Frequency Analysis Using a speech to text system, such as Whisper, translate the recorded audio to text. Analyze all words spoken and record their frequency. Then compare the patient’s speech to the dictionary to identify all diagnostic terms/keywords. Then create a rank scale symptom and sign frequency index, including such endpoints as: #times a word was used over an entire conversation, % Diagnostic term used = #times keyword used /all words; inter-word frequency of specific terms; and other endpoints TBD. Step three: Speech sematic and sentiment analysis tools – Develop semantic and sentiment analysis tools to extract meaning and emotional content to develop additional verbal quantitative biomarkers. Step four: Develop standardized report – to display data, upload to EHR or secure cloud, printout. Keywords and endpoints can be graphed and used to compare across "multiple visits" seeing how often the patient uses the diagnostic words, e.g., a patient with dyspnea reports that they are “short of breath” 15 times in their first visit. In subsequent visits they report that they are short of breath 9, 3, 1 and 0 times. This would indicate improvement. Step five: AI Assessment of Diagnosis and Therapy - Determine suggested diagnosis and next steps (diagnosis and therapy via querying open and closed Gen AI (ChatGPT 4o and Claude vs Llama)
2. Facial Affect/Mood/Happiness Indicator - using cameras and facial recognition the team will design a system to analyze mood and happiness based on facial expressive characteristics, grimace and related visual expressive signs. AI will be utilized and machine learning to refine the diagnostic readout.
3. Motion analysis tool - The team will use Google Mediapipe to record patient motion, create a visual skeleton of motion that may be played back and develop basic quantitative gait information in terms of speed, symmetry, stability, sit to stand and related variables that may be compared serially
NOTE: For all tools the team will develop: 1. a recordkeeping and display system for serial trend analysis and 2. Integrate raw and processed data into means of storage and recall from an electronic health record.

Friday afternoon mentoring sessions (for all Kidney/ACABI teams) on a rotating pre-scheduled basis will be in place to provide adequate guidance.

Project Goal/Summary: The purpose of this project to develop a functional, small footprint/point-of care analysis system to detect 1. Microplastics, 2. Heavy Metals (lead, cadmium, arsenic and mercury) and 3. Inorganics (Nitrate/Nitrite and Phosphates) i.e. “water baddies,” in water or other similar ingestible fluids; This system will reduce personal and group water risk, while serving as tool for environmental monitoring and protection. Clean Water for a Safe Future!

Project Background: Increasingly our water supply is being contaminated with pollutants from industry, waste discard and agriculture that is difficult to detect and difficult to remove. Three classes of agents: 1. small size plastic fragments and particles – plastic micro and nanoparticles, 2. Heavy metals - lead, cadmium, arsenic and mercury and 3. Inorganics – Nitrates/nitrites and phosphates are both becoming prevalent in the environment, creeping into our water supply and finding their way into ingestible water, liquids and foods. These materials present long-term hazards, not only to the individual but to society and to all higher animal life. The particular invidious nature of these materials is their long-term durability and persistence – in both water, the environment, and in the body, once ingested. These agents have been shown to induce a range of health consequences including: elevation of cholesterol levels, liver and kidney abnormalities, altered thyroid function, as well as effects on reproductive health and certain malignancy risks. This project aims at developing a simple, portable expensive system, that may be dispersed in the community – at home and in regional labs. Developing a system of harmful agent monitoring will allow a present and future look as to the state of contamination and will lend itself to corrective actions. Also, data supplied may amassed to develop large amounts of data for Big Data and Artificial Intelligence approaches to this environmental and health problem for a safer future.

Requirements: 1. Jump – in Review and define microplastics, heavy metals and inorganics – what are they, what end-organ biological damage can each induce, and what is their environmental prevalence and distribution in Arizona and around the U.S.? 2. Detection methods - For each contaminant group define the range of methods that may be utilized to detect each, their sensitivity and ease-of-use. 3. Preferred Build: Design a small footprint device with cassettes that integrate with a Smartphone and connects to a display/graphical user interface and the cloud. 4. Test strips/Cassettes (for the device- FOCUS ON PAPER MICROFLUIDIC, or CHANNEL MICROFLUIDIC DETECTION. 5. SMARTPHONE USE - for readout and data collection of strips/cassette, processing and streaming to cloud and an AI TOOL. 6. Microplastics -in particular Device will collect, detect and size - Team can benefit from work of a prior Sr Design team - use optics, small laser or electrostatic means for particle detection. 7. Homogenization with environmental standards – device/system will develop a standard form readout and report that will be in accordance with evolving EPA (Environmental Protection Agency) or other standards agencies.

Friday afternoon mentoring sessions (for all Kidney/ACABI teams) on a rotating pre-scheduled basis will be in place to provide adequate guidance.

The engineering team will design, develop, and ground-test a hybrid electric engine tailored for a future heavy-lift Unmanned Aerial Vehicle (UAV). This project will focus on creating a propulsion system that combines the efficiency of electric power with the extended range and power density of traditional fuel engines, optimizing it for heavy-lift capabilities.

The team will design a scalable hybrid powertrain integrating electric motors and internal combustion engines. The project will also involve developing control systems, energy management strategies, and thermal management solutions to ensure reliable and efficient operation during high-demand scenarios. The team will build and test a scalable hybrid electric engine to validate their design and engine control models.

The engineering team will develop and test an innovative liquid propellant rotating detonation rocket engine (RDRE). The project will focus on leveraging the potential of RDRE technology, which promises higher efficiency and reduced fuel consumption compared to traditional rocket engines.

The team will be responsible for the design, simulation, fabrication, and testing of a prototype RDRE. This will include optimizing the detonation wave dynamics and ensuring the structural integrity of the engine under operating conditions. A heavy-weight prototype will be designed and built, followed by a design-only for a flight-weight RDRE, using the results from the static test firings. The project aims to push the boundaries of aerospace propulsion technology, providing valuable research experience and contributing to the next generation of rocket engines. This project represents a unique opportunity for the university team to engage in cutting-edge aerospace research, with the potential for significant contributions to the field and real-world applications in space exploration and defense.

Determine the limits of achievable accuracy and repeatability (through extensive analysis and modeling) in measuring wafer topography in a lithography system, using an optical system other than a double-pass interferometer. Quote wavefront error as Zernike polynomials Z2-Z6. Put together a lab setup (such as a single-pass interferometer, Shack-Hartmann Wavefront Sensor, etc.) to demonstrate and verify these levels of accuracy and repeatability.

******This sponsor will not be present at Open House. If interested, please sign up for an interview slot here - https://bit.ly/ASML25037******

Surface flatness of the mating surfaces of the slew ring assembly must meet a profile tolerance of 3 mm.

Re-designed slew ring assembly must meet all Caterpillar specified stress and frequency requirements.

The re-designed slew ring assembly must fit into the same location as the current part and must maintain the same mounting features.

The design must be manufacturable.