Fundamentals of Undergraduate Research Program (FUTURE)
Would you like the opportunity to work with a mentor on a small project to see if research might be something you are interested in pursuing?
The Fundamentals of Undergraduate Research Program (FUTURE) is an exciting opportunity for first- and second-year BOLD scholars, BOLD society members, and Lattice scholars to gain practical research experience in engineering by linking undergraduate students with a graduate student mentor. Get hands-on experience as an undergrad working in a research lab alongside your mentor. You'll work on a research project 3–5 hours per week and participate in a 15-week seminar course on research practices. You'll also develop your own research hypothesis and work through the research process, culminating with a poster presentation at the end of the semester.
Applicants must maintain "Satisfactory Academic Progress" as specified by the Financial Aid Office.
Details for Undergraduate Students
- Work with a graduate mentor for 3–5 hours per week
- Gain exposure and learn the fundamentals of working in a lab environment, testing a hypothesis, and analyzing data
- Participate in a 15-week seminar course for one credit (graded Satisfactory/Unsatisfactory)
- Make a poster about your experience and present it at the end of the semester
Details for Graduate Student Mentors
- Work with an undergraduate student for 3–5 hours per week
- Gain leadership and mentoring experience, attend a workshop on mentoring, and learn how to productively integrate an undergraduate student into a lab environment. List this on your CV under teaching and mentoring experience!
- Gain an extra set of hands to help further your research
- Help your mentee design a poster to present at the end of the semester.
Check your email for the program application.
Aerospace Engineering Sciences
Project Description
This project will support our group's work on understanding the location and mass of dust impacts on the STEREO and PSP missions., therefore pushing the boundary of knowledge. This project will consist of electrostatic modeling (both through the commercial CST Studio software and python/MATLAB), optimizing the model, and comparing it to real dust impact waveforms from the missions. This role will teach some basic data analysis and modeling skills that can be applied to a number of fields. Additionally, its focus on solar missions will be supplemented by basic solar physics, space dust, and instrumentation mini-lectures given by the graduate student to enhance the learning experience.
Special requirements:
- A rudimentary understanding of electromagnetics
- Some experience with python or MATLAB
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Mechanical Engineering
Contact
Austin Smith, PhD Student
Project Description
Ideally, we have an initial spacecraft position and velocity. With this information, we can generate an orbit that informs us of all future locations of the spacecraft. In practice, we are never 100% sure what our initial spacecraft position and velocity are. Rather, our spacecraft lies in some initial volume that contains all the plausible locations at the initial time. To understand where our spacecraft could possibly end up in the future, we need to understand how the size and shape of the volume changes over time.
This project focuses on an analytical description of uncertainty volume shape and size evolution when atmospheric drag is acting on our spacecraft. The participant will utilize classical mechanics, specifically Hamiltonian mechanics, to understand volume evolution. Local pockets of space about a trajectory that act to collapse, expand, or preserve volumes will be identified, providing size and shape information.
The nature of the project is primarily analytical with numerical aspects. Specifically, the participant will validate the analytical results with numerical particle cloud simulations in a simplified near-Earth orbital environment.
Special requirements: Participants are suggested to have some basic understanding of linear algebra, calculus, and classical mechanics. Some proficiency in coding is also desired.
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Engineering Physics
Contact
Oliver Boodram, PhD Student
Project Description
Future human deep space exploration missions will require astronauts to be more autonomous than ever before. Especially during accidents and emergencies when the communications delay is too big for real-time mission support from Earth, astronauts need to be able to deal with issues by themselves. Therefore, this project aims to develop a human participant experiment that properly introduces emergency response relevant stressors and operational constraints of deep space missions in a laboratory environment.
A student on this project is expected to support the investigation of current emergency response simulation protocols established in terrestrial relevant industries (e.g., submarines, nuclear power plant operations, etc.), identify key psychophysiological stress indicators, and develop laboratory capabilities to introduce the identified stressors during human participant experiments.
Depending on the student's expertise and interests, tasks may include conducting a literature review, prototype task equipment (hardware and/or software), evaluating sensor suites for the task, and analyzing preliminary results.
Special requirements: None
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biomedical Engineering, Chemical Engineering, Chemical & Biological Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering
Contact
Patrick Pischulti, Post-Doc
Project Description
This project focuses on investigating how interactions between humans and a cyber-physical teammate can impact a human's psychological safety, human behavioral health, and performance. We will also investigate equitable and inclusive design practices for cyber-physical teammates and assess their impact on the same human constructs.
Within this project, a student will have the opportunity to contribute to the development of an autonomous agent that interacts with a human teammate during human participant experiments. Based on the student's expertise and interests, tasks may include the development of a basic robot task on the Franka Research 3 platform, the development of a basic user interface for the human participant to interact with the autonomous agent during experiments, the development of a real-time data pipeline for collecting and pre-processing sensor data, and/or investigate how to leverage existing Large-Language-Models (LLMs) such as GPT-4 for the experiment as an additional teammate.
Special requirements:
- Students should have an interest in AI/ML algorithms and prototyping (hardware and software)
- Some prior exposure to software development (ideally in Python but not required)
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biomedical Engineering, Chemical Engineering, Chemical & Biological Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering
Contact
Patrick Pischulti, Post-Doc
Project Description
This project will focus on the development of the Passive Autonomy, Navigation, Topography, and Habitability Exploration Radar. The main goal for the student will be to program a prebuilt power distribution board to meet the system requirement and integrate the board into the radar system. This requires multiple parts to work together and communicate in order to provide the proper power to the equipment and powering the computer itself. The final product will be an embedded solution to retrive data of a software defined radio while deployed on a drone platform. In addition to programming the power distribution board, the studen't may work with the PhD student on assembly and design of the radar system as time allows.
Preferred Qualifications:
- Embedded programming of microcontroller using Python or C++
- Understanding of basics of electronic circuits and the use of electrical equipment such as multimeters, oscilloscopes and powersupplies.
Website: https://stpeters54.wixsite.com/my-site/research
Desired majors: Aerospace Engineering Sciences, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Mechanical Engineering
Contact
Thorsteinn Kristinsson, PhD Student
Project Description
The study of differential equations gives a certain credence to Galileo's famous claim that "math is the language of the universe." Though many phenomena in the natural and human worlds do not fit neatly inside this conceptual framework, the scope of differential equations is quite impressive. Electrical circuits, magnetic fields, heat transfer, fluid flow, and the deformation of solids are all elegantly described by differential equations which relate inputs we control--things like heat flux or force--to rates of change in quantities we care about--things like temperature or position. Because of their ubiquity in science and engineering, it is important to be able to solve differential equations. But solving differential equations is often impossible without recourse to approximate solution methods implemented in computers, and techniques from machine learning have emerged as promising alternatives to more traditional approaches. In this project, the student will get exposed to research in computational physics and machine learning by deriving and writing code in MATLAB or Python to solve differential equation of their choice using neural networks and optimization methods.
Special requirements:
- The student must have taken a course in differential equations
- The student should enjoy math/physics and understanding fundamentals
- The student should have some scientific programming experience
- The student should be excited about developing code of their own, as opposed to running existing code
- The student should be motivated and curious (most important)
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Civil Engineering, Computer Science, Electrical Engineering, Engineering Physics, Mechanical Engineering
Contact
Conor Rowan, PhD Student
Project Description
GPS/GNSS technology is something we use every day, but we usually only see the final position result. In this project, we'll take a step back and explore the raw data behind those results -- the data that makes GPS/GNSS positioning possible. Using a U-blox receiver, we'll collect GPS/GNSS measurements, convert that raw data into formats we need to calculate positions, and then break down what kind of information is hidden inside. To help with this, we'll be using an open-source tool called RTKlib.
Learning how to access, understand, and work with raw data is the first and most important step in GPS/GNSS research. This project will give students a solid starting point, providing the key skills needed to dive deeper into GPS/GNSS technology in the future.
Special requirements: Open to everyone who is interested in GPS/GNSS.
Desired majors: Aerospace Engineering Sciences,Computer Science,Electrical Engineering,Electrical & Computer Engineering
Contact
Joo Han Chun, Master's Student
ATLAS
Project Description
This project will focus on validating the structural and functional subcomponents of a complex DNA origami nanomachine. The student researcher will be expected to create various mixtures for self-assembly reactions corresponding to different versions of a DNA origami nanomachine, then verify self-assembly using gel electrophoresis. Some functional components of the nanomachine will include the incorporation of enzymes such as polymerases or exonucleases. As a complete nano-synthesizer will rely on multiple immobilized enzymes working together, the student researcher will be in charge of ensuring each enzyme works separately, then verifying attachment to the DNA origami, then verifying each enzyme works together as various various subcomponents of the nano-synthesizer begin to take shape. Additionally, the student researcher will learn to process and present data in a clear and effective manner.
Special requirements: Students should have an interest in interdisciplinary research with a track record of completing projects in a timely and efficient manner
Desired majors: Biomedical Engineering, Chemical Engineering, Chemical & Biological Engineering, Computer Science, Creative Technology & Design, Engineering Physics, Integrated Design Engineering, Mechanical Engineering
Contact
Joshua Johnson, Post-Doc
Project Description
This research proposal aims to enhance electronics-integrated textiles (e-textiles) development by introducing a tool for designing pockets, a complex woven structure that supports wire routing and components integration. Enabling applications from smart sensing in space suits to soft robotics, this tool will become a new feature inside an existing parametric weaving design tool, adding to the open-source ecosystem. Through design, implementation, and evaluation phases, the goal of this project is to increase access to complex weaving through pockets and pave the way for future innovations in textile simulations and electronic integration in woven textiles.
As an undergraduate researcher, possible tasks may include and are not limited to: software development towards multilayer woven structures; sampling woven designs on a TC2 digital loom; user testing, documenting, and reporting bugs in software development; and ideating and testing new e-textiles application areas for the tool.
Special requirements: We hope to find a student who has interest in the topic (computer science, art/design/craft, electrical engineering) and are happy to train them to get up to speed. Prefer a sudent who has prior experience with weaving.
Website: https://unstable.design/adacad-3/
Desired majors: Aerospace Engineering Sciences, Biomedical Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Integrated Design Engineering, Mechanical Engineering
Contact
Deanna Gelosi, PhD Student
Project Description
The project aims to synthesize functionalized hydrogel particles in micron scale dimensions and to study their self-assembly for different biochemical applications. The student will be actively involved in synthesis of polymeric hydrogel particles by UV-photopolymerization via a state-of the art photolithography setup. The hydrogels are supposed to be in micrometer scale and have some functionality to self-assemble. The project also involves monitoring the physicochemical properties of the microparticles and conditions for self-assembly. There is another interesting part in this project involving fabrication of microfluidics and micro-environments for observing the self-assembly of microgels. The student will perform microgel synthesis and characterization, potentially including image analysis, nano-fabrication techniques, optical and electron microscopy, testing different mechanical properties and dynamic mechanical analysis.
Special requirements: Knowledge of basic chemistry (GEN-CHEM) and polymer is plus.
Website: https://www.emergentnanomaterials.com/
Desired majors: Biomedical Engineering, Chemical Engineering, Chemical & Biological Engineering, Environmental Engineering, Mechanical Engineering
Contact
Subhankar Mandal, Post-Doc
Chemical & Biological Engineering
Project Description
Bipolar membranes (BPMs) have undergone a renaissance thanks to advances in polymer science, water catalysis, and low-cost renewable energy. Typically, BPMs were predominately found in acid-base (re)generation applications, however, their ability to tune pH gradients and ionic fluxes have made them a promising technology to improve a wide range of electrochemical processes. For this project, our objective is to use continuum modeling to better understand BPM physics to provide insights into BPM design and operation to enhance overall performance. In particular, we are interested in increasing the efficiency by CO2 capture and utilization technologies from our studies.
For this project, the student will learn how to conceptualize and define modeling domains and other necessary variables to accurately represent BPMs. The student will be introduced to numerical techniques to solve the Poisson-Nernst-Planck equations. Student will also help with literature review to compare model results with other existing models and experimental data. Students can help with create figure schematics and data visualization for modeling results. There are potential opportunities for publications.
Special requirements:
- Student should have solid math background, but doesn't need to be familiar with the specific techniques that will be used - asymptotic matching and perturbation analysis.
- Students must have at least introductory-level knowledge of Python coding.
- Student should have general knowledge of chemistry and transport phenomena. Even better if they understand basics of chemical kinetics.
- Student can work remotely, but it is highly encouraged that on-boarding and fundamental learning be done in person.
Desired majors: Applied Mathematics, Chemical Engineering, Chemical & Biological Engineering, Engineering Physics, Mechanical Engineering
Contact
Peter Romero, PhD Student
Civil, Environmental & Architectural Engineering
Project Description
CDOT Research Title: Evaluation of Carbon Reduction Technology's Impact on Concrete Performance and Life Cycle Emissions
Funding Source: State Planning and Research (SP&R)
Background:
Many technologies have been promoted to reduce greenhouse gas (GHG) emissions of concrete mixtures. Some technologies, such as nano-silica (SiO2) and carbon black nanoparticles, promote the improved environmental impacts of the concrete based on increased concrete strength, improved water penetration resistance, and/or increased longevity. Another type of new technology, carbon capture and storage (CCS), proposes capturing carbon in fresh concrete through pressurized CO2 curing and then retaining the carbon within the hardened concrete through carb
The objectives:
1. Analyze the long-term performance of concrete incorporating new environmental impact reduction technologies, including nano-silica, carbon black nanoparticles, and Carbon Cure, using standardized concrete durability and strength laboratory tests.
2. Based on the results of the laboratory tests and pre-existing studies, perform Life Cycle Assessment (LCA) to evaluate the GHG emissions of the concrete modified by the new technologies.
Special requirements:
General Requirements:
- All personnel involved in this project shall be required to adhere to the requirements of Procedural Directive No. 0080.1: Personal Protective Equipment Use in performing any necessary field work.
- CDOT, in accordance with the provisions of Title VI of the Civil Rights Act of 1964 {78 Stat. 252, 42 US.C. §§ 2000d to 2000d·4) and the Regulations.
- The reports, data analysis, results, and other information generated by the proposer as part of the study shall become the property of CDOT.
Additional Preferred Qualifications:
- Laboratory Experience or a strong interest in gaining hands-on experience in a research lab
- Willingness to participate in weekly concrete lab work (moderate physical tasks)
- Fieldwork Capability for additional data collection
- Availability to work 3 hours weekly and attend bi-weekly update meetings (included in weekly hours)
- Commitment to the project over an extended period (up to 12 months, if possible), providing valuable research experience
Desired majors: Architectural Engineering, Civil Engineering, Creative Technology & Design, Environmental Engineering, Integrated Design Engineering
Contact
Suttichai Charoenkij, PhD Student
Project Description
Increasingly large wildland fires have threatened Colorado's landscape in recent years, challenging infrastructure in both rural and urban areas. While guidance documents exist to help drinking water treatment operators respond to wildfire risk, there is no centralized guidance to advise wastewater treatment operators responding to associated hazards of wildfire, including interrupted supply chains, damage to distributed infrastructure like pump houses and sewer lines, and altered wastewater chemistry. A series of interviews were conducted by Ph.D Candidate William Johnson to evaluate the preparedness of wastewater operators for wildfire risks. The FUTURE student will collaborate to code these interviews for major themes identified by wastewater operators. Additionally, the FUTURE student will compare the concerns identified by wastewater operators with existing emergency guidance documents. This project is an introduction to qualitative research and may result in a journal publication.
Special requirements: The student must be able to meet for a two-hour block at least once a week. If the student has no background in qualitative research methods, the first several sessions will be spent reviewing online training materials.
Desired majors: Architectural Engineering, Civil Engineering, Environmental Engineering
Contact
William Johnson, PhD Student
Project Description
This project is part of an ongoing study to understand the potential of fires at the wildland-urban interface (WUI) to contaminate surface water sources. The specific focus of the work is to assess the applicability of using online sensors at water treatment plants to monitor levels of pyrogenic contaminants using optical techniques, such as absorbance and fluorescence, after specific treatment processes, such as filtration and coagulation.
This project is designed to introduce students to a variety of chemical analytical techniques, including dissolved organic carbon (DOC), UV-Vis absorption, and fluorescence, as well as water treatment-specific techniques, such as jar testing. The interested student will assist with preparation steps for processing of samples prior to chemical analyses (e.g., combustion of raw materials, leaching of prepared ashes) and be trained to independently operate UV-Vis and DOC instruments while shadowing other analyses. Emphasis will be further placed on exposing the student to experimental design, data analysis methods, and communication of results.
Special requirements: The student must be available to work on both main and east campus in 2-hour blocks (though availability can be flexible regarding day of the week and time of day). Students should have taken General Chemistry with a lab component, though Water Chemistry and/or Environmental Organic Chemistry are a plus.
Desired majors: Chemical Engineering, Chemical & Biological Engineering, Environmental Engineering
Contact
Mackenzie Bowden, PhD Student
Project Description
The student will help with wildfire research; mainly examining particulate matter. This research will be mostly online and the student will focus on data analysis of measurements collected in people's homes during wildfire season. There will be opportunities here and there to work in the lab or the field co-locating particle measurement machines. The student will process data in Matlab looking at smoke infiltration rates and particle size distributions.
Special requirements: Student must have experience in Matlab.
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biomedical Engineering, Chemical Engineering, Chemical & Biological Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering
Contact
Rileigh Robertson, PhD Student
Computer Science
Project Description
Modern Machine Learning (ML) models have achieved exceptional performance on various tasks once considered exclusive to human intelligence. Much of this success, however, is attributed to "scaling up" — increasing the size and complexity of ML models. This complexity has fueled the emergence of eXplainable Artificial Intelligence (XAI), a field aimed at understanding the internal processes driving these models' decisions.
In recent years, Large Language Models (LLMs), such as ChatGPT, have seen widespread public use. Despite their impressive capabilities, LLMs are prone to "hallucinations," where they generate fabricated or incorrect information. While LLMs can provide explanations for their outputs, there is no guarantee that these explanations are reliable or truthful. To address this issue, we aim to investigate how LLMs interact with their environment and how to assess their reasoning and decision-making processes.
Our goal is to design a sequence of tasks that can help practitioners evaluate the capabilities and limitations of these models, similar to how humans are tested in exams or interviews to gauge their knowledge and abilities. A key question guiding this research is: Although ML models are trained on human-generated data, they may not share our intuitive understanding of it. How can we design tasks that reveal how models arrive at their decisions, and how can we ensure that these tasks effectively probe their reasoning
Special requirements:
The main requirement is coding ability in Python and a willingness to learn.
Prior exposure to Probability will be helpful.
While this project is about Machine Learning, we do not require the student to have taken a course in ML. However, prior experience (coding or math related in ML) would definitely be very helpful.
Desired majors: Applied Mathematics, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics
Contact
Amit Kiran Rege, PhD Student
Project Description
We are studying the why people are susceptible to misinformation and how this is affected by their information environment. In the spring, we will be collecting data for a couple of experiments to answer these questions. We are focusing on small teams doing Mars rover reconnaissance using a simulated 3D environment and physical Mars rover mock up. The experiment includes several sensors: fNIRS, EEG, heart rate, eye-tracking, microphones and video. You would have the opportunity to learn how to use all those sensors if you'd like to help with data collection, and we could go over data processing too. We will also have a machine learning component starting up later in the semester but that's optional. We also have a field version of the study that'll be taking place at the Mars Desert Research Station, and an fMRI version that I could use help planning so depending on your workload, you could help with those too!
Special requirements: If you want to help collect data, this will likely require 2 hr blocks of time. Also, previous coursework related to neuroscience or experience with any of the sensors is highly recommended. If you're interested in machine learning on human physiological data, coursework or example projects related to that is recommended.
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Biomedical Engineering, Computer Science, Creative Technology & Design, Integrated Design Engineering
Contact
Cara Spencer, PhD Student
Project Description
The core focus of this project involves programming robots to nonverbally express emotions while performing tasks.
When a robot is performing a task, we want it to execute trajectories that express certain emotions with high clarity and robustness.
The application of this research revolves around Human Robot Interaction (HRI).
A few examples include:
1) When a robot is performing a high-risk task, the robot can express anxiety/fear.
2) When a robot succeeds at a task, it can express happiness/joy.
3) When a robot does not succeed, it can express sadness/guilt.
As of now, there are two prospective approaches we have in mind:
1) We can leverage machine learning to train models that can map certain emotions to robot trajectories and choose the ones that ensure task completion without compromising on the quality of expression.
2) We can use laban movement analysis (LMA) for deterministically mapping robot parameters to certain expressions and use it with a motion planning algorithm to plan expressive paths.
The student is expected to help us in simulation and real-world experiments, writing code and paper writing. We aim to publish this work to a top robotics conference.
Special requirements:
It would be helpful if the student has a good knowledge and experience regarding one or more of the following:
1) Python
2) Machine Learning/ Deep Learning
3) Introduction To Robotics
4) Motion Planning
5) Robot Operating System (ROS)
I will be teaching the students from scratch if they aren't familiar with these. However, if a student does have prior experience, it's a bonus.
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Biomedical Engineering, Chemical & Biological Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering, Mechanical Engineering
Contact
Srikrishna Bangalore Raghu, PhD Student
Project Description
Implantable medical devices collect a myriad of patient data, yet patient therapies are typically defined for the average patient. Therapy tailored to the individual patient is possible by applying the inherent creative exploration of reinforcement learning (RL) to find patient optimal device settings. This research project is a joint effort with the Anschutz medical campus focused on application of RL safely in medical devices to improve patient quality of life.
A student team member should have a basic understanding of RL network design and the ability to extend that knowledge to less common architectures such as Hebbian. The student would be fully integrated with and support the team with tasks including creating simple computational models of biological processes, coding and training RL networks, medical data analysis, and presenting reviews of research papers. This is a project for someone with interests in biomedical and AI wanting to dive deeper through real world applications.
Special requirements: Must have experience with Python.
Desired majors: Biomedical Engineering, Chemical & Biological Engineering, Computer Science, Electrical & Computer Engineering
Contact
John Komp, PhD Student
Project Description
The Correll Lab is exploring a unified system for mobile manipulation in the open world. Within this broad effort, we've identified semester-long projects suitable for undergraduate researchers, such as:
- Deploying and benchmarking new computer vision models & methods on our custom robotic tasks (either with a provided dataset or by collecting data from real-robot experiments)
- Designing user interfaces and user experiences for our front-end Human-Robot interface (more similar to UI/UX development on our existing interface)
- Reading papers and presenting new techniques to the group (a la survey papers).
- And more! We will work closely with the student to understand their interests and background in order to form an appropriate project.
We will work together to define concrete "completion" points of the project and make it an encapsulated experience, but much of this work can be and often is incorporated into larger published work, providing avenues for authorship if the student is motivated.
Special requirements:
Preferred:
- Python programming experience
Ideal:
- Familiarity with linear algebra (matrix operations)
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Biomedical Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering, Mechanical Engineering
Contact
William Xie, PhD Student
Engineering Physics
Project Description
The Boulder Cryogenic Quantum Testbed is an experimental quantum physics lab that specializes in the measurement of superconducting qubits and resonators. These devices are measured in a dilution refrigerator that can reach temperatures as low as 10mK.
Currently, we are in the process of characterizing, calibrating, and optimizing our cryogenic measurement setup to improve the precision of our measurements. For us to achieve this, we need to understand every single component in our system. The student will work with the mentor to develop a measurement protocol, learn how to measure each device, and create a strategy for archiving data.
The takeaways we have for our student include gaining experience working in an experimental quantum physics lab, hands-on work with a dilution refrigerator, measuring devices using a VNA, and general knowledge on how RF/microwave measurements for physics research are done. We also will help the student learn object-oriented coding in Python, whether they are familiar with it or not.
Our expectations for the student include a willingness to learn despite the challenges faced and that the student ask as many questions as they possibly can.
Special requirements: Our lab is very flexible, we can work with the student's schedule and workload to schedule physical lab time and physical/virtual coding time.
- Strong desire to practice coding in Python for measurements in an experimental quantum physics lab
- Interested in how to use a terminal in coordination with Python to do routine measurements of several devices
- Interested in possibly implementing a raspberry pi as a control device
- Familiar with basic circuit theory, e.g. what is a resistor/capacitor/inductor, and how they are related to impedance, in order to:
- Learn what S-parameters are, and how to measure them
- Once the student has learned what S-parameters are, they will record the S-parameters of several devices and organize them into an archive for future reference
- Learn what S-parameters are, and how to measure them
- Has taken any lab course, so that they are willing to learn how to:
- Connect, disconnect, and safely handle microwave/RF components that are sensitive to damage from ESD
Preferred:
Python programming experience
Ideal:
Familiarity with linear algebra (matrix operations)
Desired majors: Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Mechanical Engineering
Contact
Jorge Ramirez Ortiz, PhD Student
Environmental Engineering
Project Description
Pharmaceuticals are critical to human health, but when they enter the environment, often through wastewater treatment plant (WWTP) discharges into local surface water, they become contaminants. Pharmaceuticals in the environment are toxic to aquatic organisms, facilitate antimicrobial resistance, and are difficult to remove from wastewater without advanced treatment, which is often unavailable in disadvantaged and/or rural areas. This also makes new developments in sustainability practice such as wastewater reuse more difficult. SeweRx is an app currently under development to predict pharmaceutical concentrations during wastewater reuse. This project will focus on data collection and processing to support the refinement of the predictive model within SeweRx during transport from toilet to WWTP and during different wastewater treatment processes. The student will gain experience in conducting systematic literature searches, the data mining pipeline, and implementation and evaluation of predictive models. Special focus will also be placed on the environmental justice issue of pharmaceuticals in the environment and ethical considerations for use of wastewater data.
Special requirements: Student must have at least intro-level coding experience. R, Python or MATLAB preferred but not required. No other experience required; the mentor will teach any other skills needed.
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biomedical Engineering, Chemical Engineering, Chemical & Biological Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering
Contact
Vanessa Maybruck, PhD Student
Materials Science and Engineering
Project Description
The project involves creating fiber structures using cells and biopolymers by extrusion bioprinting. The cells are filamentous fungi cells, also known as mycelia. These cells are chosen because they grow rapidly and possess a unique radial growth from the printed fiber as the organism searches for nutrients. They can be grown from both solid and liquid culture, with varying growth rates. The radial growth/extensions of the organism (hyphae) are critical for tuning the desired mechanical properties of the fiber structure. These properties will be controlled by the length of the hyphae, which is directly influenced by the growth time. Therefore, it is of interest to characterize the growth of the hyphae extensions, by printing cells into fibers and observing the growth over time. The fiber samples will be imaged using a PhotoBox set-up along with Image Analysis to quantify the growth rate. Different cell densities will be chosen for the prints to additionally determine the impact of density on growth rate.
Key Responsibilities: Solid and liquid cell culture techniques, Extrusion printing biopolymers and cells to create fiber structures, Imaging/Image Analysis
Special requirements:
- Available for two 2-hr blocks during normal business hours (M-F 9-5pm).
- Sophomore level or above preferred.
Desired majors: Biomedical Engineering, Chemical Engineering, Chemical & Biological Engineering, Civil Engineering, Engineering Physics, Environmental Engineering, Mechanical Engineering
Contact
Olivia Pear, PhD Student
Mechanical Engineering
Project Description
In my role working in an air quality lab that primarily centers research, I also have a unique opportunity lab to develop low cost sensing packages. To do this, I run a team called the development team in this lab. This team builds PCB's, assists a large number of air quality researchers in maintenance and preparation of their tools, and aids in outreach and education. In this particular role, the student would work with us to iterate on previous projects' designs and build small sensing packages. Furthermore, there will be opportunities to aid in multiple research projects by participating in field work, working in electronic trouble-shooting, and assisting in assembly of sensing packages.
Special requirements: Students must have interest in the sustainability field, and an interest in learning practical electronics through hands-on opportunities. Furthermore, I'm working in engineering education, and especially remain interested in engineering ethics, so if any students happen to have interest in those fields, I have found that to be a uniting factor in this cohort of undergrads that I work with.
Desired majors: Aerospace Engineering Sciences, Creative Technology & Design, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering
Contact
Percy Smith, Master's Student
Project Description
Photoelasticity is the change in optical properties of a material under mechanical deformation. This gives a way to use imaging to determine the stresses and forces acting on an object. In practice, deforming a photoelastic particle creates a fringe pattern that is unique to the mechanical loading. We study granular flow by using high-speed imaging to analyze the stresses and forces on 2D cylindrical particles interacting with each other and their environment. The key phrasing here is “2D cylindrical particles.†Complex particle shapes will lead to photoelastic fringe patterns that are difficult or impossible to mathematically define a closed form solution. In this project, a student will experimentally study the photoelastic response of additively manufactured 2D complex particle shapes, such as a square, trapezoid, triangle, and custom shapes. The sample will be placed between two polarizers and loaded into an Instron mechanical tester to apply forces. Images will be taken at discrete amounts of mechanical load to measure the photoelastic response of the samples. A student can expect to become familiar with imaging, photoelasticity, mechanical testing, and image processing.
Special requirements: While not required, there is a potential to relate the physics to the experimental results which will involve more complex mathematics for those of interest. No special requirements.
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biomedical Engineering, Chemical & Biological Engineering, Civil Engineering, Engineering Physics, Environmental Engineering, Mechanical Engineering
Contact
Brandon Hayes, Post-Doc
Project Description
CU scientists have been asked by the local organization EcoArts Connections to collaborate on the community-based project "Vecinos (Neighbors)," which seeks to address
environmental injustice issues of air and water quality in mobile home/manufactured housing communities (MHCs). Vecinos’ mission is to inspire action on environmental justice
issues through the arts. Vecinos will be based at San Lazaro (SL) MHC, with air quality measurements and water quality education from the surrounding “neighborhood.” Vecinos, in
combination with an Artivismo (art and activism) summer camp, brings together CU faculty and students with community members including San Lazaro MHC residents (kids to
seniors), artists, city and county officials, policymakers, and others in a series of activities to increase experiences and understanding about the lack of healthy air and water quality
unfairly experienced by underserved immigrant (mostly Latinx) people living at or below the poverty line. Activities will include community meetings, air quality monitoring, and data analysis, making art out of smog workshops, talks, an exhibition at SEEC, an Artivismo summer camp - created especially for SL.
Special requirements: It is preferable that the student speak some Spanish and have a car. Should also be able to work in 2 hour blocks.
Desired majors: Environmental Engineering, Mechanical Engineering
Contact
Allison Fagerson, PhD Student
Project Description
Our lab focuses on advanced batteries for energy storage. We frequently use thin films (< 5 nm) synthesized via Atomic and Molecular Layer Deposition (ALD/MLD) to tune the surfaces of advanced battery materials to shut down unwanted side reactions.
We found that combining layers of two different films leads to unexpectedly high performance in certain systems. We have some educated guesses as to why the films work well together but do not fully understand all of the chemistry involved. There are many trials to be attempted and we need help ruling out certain avenues.
The student involved with this project will help with (1) preparing electrodes for li-ion batteries, (2) coating them with thin films via MLD/ALD using previously established recipes, and (3) assembling batteries in a glovebox for cycling. The student will help isolate the possible origins of the effect and directly contribute to the realization of more advanced batteries.
This project is an opportunity to gain practical hands on experience working on topics around electrochemistry, thin films, and batteries. These are marketable skills for any engineer interested in technical industry roles or graduate school.
Special requirements:
- Students must have taken at least one practical chemistry lab course and be comfortable with basic chemistry.
- Previous education in electrochemistry or organic chemistry would be highly beneficial but is not required.
- The ideal student is interested in renewable energy, chemistry/materials science, and gaining hands-on experience.
- For coursework, it would be somewhat preferable if students have some kind of understanding of basic mass transfer. This is very much in the realm of chemical engineering, environmental engineering, and materials science, so students from those majors may be the most interested in this project.
Desired majors: Chemical Engineering, Chemical & Biological Engineering, Electrical Engineering, Mechanical Engineering
Contact
Jackson Pope, PhD Student