Summer Undergraduate Research Fellowship Project Descriptions

Faculty Mentor: Scott Strong | Applied Mathematics and Statistics

Project Abstract: 

Through a 2022 Mines SURF project, we established a connection between the autonomous flow of vortex filaments, which are geometric primitives in quantum liquids[1], finite wing theories[2], and fluid computers[3, 4, 5], and a fully nonlinear integrodifferential equation of Schrodinger type[6]. These settings are characterized by having strongly localized vortex structures in fluids with large Reynolds number. Interestingly, the same theory can also be applied to the nonlinear evolution of stiff polymers in low Reynolds number environments and is applicable in modeling liquid crystals, supercoiling in DNA, and cell motility. In the latter case, an essential analytic result connects swimmer speed to the motion of helical waveforms on an infinitely long inextensible elastic cylinder. [7, 8] Consequently, in both settings, the dynamics of curvature waves traveling along the filaments can be analyzed directly with this family of Schrodinger equations. The goal of this project will be to further develop this theory by investigating the literature connecting the two seemingly disparate models, analysis of the nonlinear dynamics of curvature waves propagating on filaments, and generation by random flagellar swimming in three-spatial dimensions whose walk properties are informed by our filament analysis.

[1] Quantized vortex dynamics and superfluid turbulence: https://link.springer.com/book/10.1007/3-540-45542-6

[2] https://web.stanford.edu/~cantwell/AA200_Course_Material/AA200_Course_Notes/AA200_Ch_12_Wings_of_Finite_Span_Cantwell.pdf

[3] https://terrytao.wordpress.com/2014/02/04/finite-time-blowup-for-an-averaged-three-dimensional-navier-stokes-equation/

[4] Cascade leading to the emergence of small structures in vortex ring collisions: https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.3.124702

[5] Potential singularity mechanism for the Euler equations: https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.1.084503

[6] Hasimoto transformation of general flows expressed in the Frenet frame: https://www.sciencedirect.com/science/article/abs/pii/S0168927423000120

[7] The action of waving cylindrical tails in propelling microscopic organisms: https://royalsocietypublishing.org/doi/10.1098/rspa.1952.0035

[8] Sperm Motility: Models for Dynamic Behavior in Complex Environments: https://link.springer.com/chapter/10.1007/978-3-319-96842-1_7

Student’s role and learning objectives: 

The successful applicant will be expected to learn how to work independently and keep records to efficiently report progress. Outside of these growth objectives, the student will also learn about the physical settings contextualizing the results of differential geometry applied to space curves, the statistical analysis of random walks in R, and wave motion in nonlinear media. To support this endeavor, the principle investigator will mentor the undergraduate researcher through weekly meetings where reporting, reflection, and planning will be emphasized. While a strong understanding of multivariate calculus and differential equations is required, familiarity with linear algebra and partial differential equations is helpful but not required.

Faculty Mentor: Cecilia Diniz Behn | Applied Mathematics and Statistics

Project Abstract: 

Reduced insulin sensitivity is associated with metabolic dysregulation, but insulin sensitivity may vary across liver, muscle, and fat tissues. Experimental protocols using stable isotope tracers in conjunction with mathematical models can be used to quantify tissue-specific insulin sensitivity, but these methodological approaches must be tailored to specific participant populations. In this project, we will work with data from adolescent girls to establish characteristics of tissue-specific insulin sensitivity under different disease and drug conditions. The project will require work with raw mass spectrometry data, implementation of a differential-equations-based mathematical model of glucose-insulin dynamics that separately describes glucose released by the liver and glucose ingested during an oral glucose tolerance test, and statistical analysis of findings.

Student’s role and learning objectives: 

Undergraduate student will undertake all aspects of this project in a mentored setting. Student should have some familiarity with mass spectrometry data, mathematical modeling, and parameter estimation, and student learning objectives will focus on developing expertise with these topics in the context of this research project. Student will be part of an interdisciplinary team involving both mathematicians and physician-scientists. My mentoring will include weekly one-on-one research meetings, weekly research group meetings, and occasional research team meetings that involve all participants in this research project. Student will also have the opportunity to be mentored by graduate students in my group who are working on related problems in mathematical modeling of metabolism.

Faculty Mentor: Melissa Krebs | Chemical and Biological Engineering

Project Abstract: 

The growth plate (or physis) is a cartilage region at the end of all long bones in children that provides signals for bones to lengthen during development; when injured, bony tissue can form in the growth plate, resulting in a “bony bar” that can cause deformities or even completely halt bone growth. This project aims to investigate the development of biomaterial systems that are capable of blocking the angiogenic processes that contribute to the formation of the bony bar. The impact of the extracellular matrix environment on this process will be investigated through the modification of the biomaterial delivery systems with anti-angiogenic peptides and extracellular matrix molecules.

Student’s role and learning objectives: 

The undergraduate student will be involved with biomaterial fabrication, characterization, and cell culture testing. The undergraduate student will be directly mentored in the lab by a graduate student, and both of these students will be mentored by the PI. We will have weekly project meetings, and we will have ready communication available via slack and/or email and/or phone calls between the meetings.

Faculty Mentor: Nanette Boyle | Applied Mathematics and Statistics

Project Abstract: 

Hormonal birth control has been around for 50+ years and has been known to increase the risk of venous thrombosis in women. Unfortunately, the exact mechanism that causes this increased risk of blood clots is not known. In the Boyle Lab, we are using isotope assisted metabolic flux analysis to measure carbon fluxes in human platelets and how they change in after treatment with estrogen and estrogen metabolites.

Student’s role and learning objectives: 

The ideal student for this project will be able to work in a BSL-2 laboratory working with blood. The undergraduate will assist the PhD student, Sami Siska, in washing platelets, performing flux analysis and measuring uptake and excretion rates using a biochemical analyzer. Since we are working with limited samples from human subjects, the student should be very conscientious and willing/able to follow detailed protocols.

The main learning objectives for this project is to learn about central metabolism in human cells, how to use a biochemistry analyzer and how to communicate in science.

The student will be supervised directly by the Ph.D. student, participate in weekly group meetings and formally present to the Boyle Lab group once during the summer. During group meeting, the student will be able to report progress, discuss troubleshooting and plans for the following week.

Faculty Mentor: Amadeu Sum | Chemical and Biological Engineering

Project Abstract: 

This research focus on understanding the molecular processes involved in the assembly of water and gas molecules to form clathrate structures. We use molecular simulations to follow the motion of the molecules, which under proper temperature and pressure conditions, can order to form cage structures. The initial process of ordering of the molecules leading to a critical size is known as the nucleation. The nucleation is the nascent cluster of molecules for a phase transformation. Our interest in clathrate hydrates is to study the fundamental thermodynamics and kinetic molecular projects that causes molecules to transition from one phase to another. Clathrate hydrates are a unique solid phase of water combined with gas playing an important role in energy storage, energy transportation, and energy transfer. This work solely computational and will expose the student to molecular simulations, molecular visualization, and big data analysis.

Student’s role and learning objectives: 

Qualifications: 
Students should have a desire to learn and especially interest in working with computer, programming, and simulations. It is also useful to have a good knowledge of thermodynamics.
Time Commitment (hours per week):
30-40 hours/week
Skills/Techniques Gained:
Students will gain skills on solving problems, computational skills, and big data analysis. Students will also be exposed to high-performance computing.
Mentoring Plan:
Regular weekly meetings will be scheduled with the students to develop the project and establish a regular timeline for progression.

Faculty Mentor: Colin Wolden | Chemical and Biological Engineering

Project Abstract: 

Ammonia is the leading carrier for distribution of green hydrogen. However to be used it must be efficiently decomposed back to hydrogen and nitrogen.
Current high efficiency catalysts for ammonia decomposition are based on the platinum group metal ruthenium. The goal of this project is to develop perovskite-based catalyst employing Ni or Co as low cost alternatives. These compounds are produced through combustion synthesis. The catalyst would be tested and integrated into our catalytic membrane reformer and baselined to a commercial Ru catalysts.

Student’s role and learning objectives: 

The student would learn how to synthesize the catalysts, characterize the catalyst using techniques such as XRD and BET, and finally test its performance for ammonia decomposition in a a differential reactor. The UG would work with three graduate students and the faculty mentor to learn the techniques involved and how to appropriately analyze the results.

Faculty Mentor: Stephanie Kwon | Chemical and Biological Engineering

Project Abstract: 

This project proposes to develop synthetic methods based on atomic layer deposition (ALD) to nano-structure microporous void environments in solid catalysts to promote their catalytic reactivity, selectivity, and stability. A successful demonstration of the proposed work will provide a novel synthetic method to fine-tune the microporous void environments in solid catalysts. We aim to systematically vary the void structures that confine relevant organic molecules and the assessment of their consequences on catalytic activity, selectivity, and stability for biomass conversions. In doing so, this work will show how to engineer the void environment in solid catalysts to provide a “tight fit” between the void and the relevant transition state for improved catalytic performance.

Student’s role and learning objectives: 

The student will work in the lab to understand the effects of synthesis parameters on the samples. The student will gain hands-on experience in inorganic synthesis and kinetic measurements (i.e., reaction engineering and catalysis). The student will work closely with the Ph.D student mentor.

Faculty Mentor: Alex Pak | Chemical and Biological Engineering

Project Abstract: 

Nanobodies, which are recombinant antigen-binding domains found in camelid heavy chain antibodies, have several advantages as therapeutics over monoclonal antibodies, including higher stability, higher solubility, and smaller sizes, the latter of which facilitates hidden epitope recognition, purification, and delivery. We are interested in leveraging nanobodies to target virulence factors in pathogenic bacteria, e.g. bacterial surface layer (S-layer) proteins that self-assemble into two-dimensional, para-crystalline, and nanoporous coats around bacterial cell envelopes. Recent work has shown that nanobodies are able to depolymerize S-layers and prevent pathogenesis, although the mechanisms of action for nanobody-induced S-layer disassembly remain unknown while strategies for their broader use remain unclear. In this SURF, the goal is to create a machine learning classifier combined with molecular dynamics simulations to predict the epitope and binding pose of nanobodies on S-layer proteins. Research in this area will support our long-term goal to computationally design nanobodies that target S-layers to disarm antibiotic-resistant bacteria.

Student’s role and learning objectives: 

The student will read through the literature, curate data from antibody/nanobody databases, assess protein-protein interfaces, train data-driven classifiers, and prepare/run/analyze molecular simulations.

The learning objectives include:
• How to curate data and how to design and train classifiers
• How to prepare, run, and analyze molecular dynamics simulations
• How to use high-performance computing resources and the Linux operating system
• How to manage computational workflows (Git, lab notebooks, scripts, etc.)
• How to code in Python and Bash
• How to critically read the literature
• How to prepare and deliver oral presentations

The student will give brief updates over Slack once a week and have an extended meeting (joint with other group members in the same research area) with the PI every two weeks. The student will also participate in regular biweekly group meetings. The group members and PI will be accessible both in-person and via Slack.

Faculty Mentor: Alex Pak | Chemical and Biological Engineering

Project Abstract: 

Hydrogels, which are cross-linked matrices of hydrophilic polymers with the propensity to hold water and solutes, can be deployed as drug delivery systems, especially when increased solubility, targeted delivery, or controlled release kinetics are required. We are interested in designing thermo-responsive coiled-coil-based hydrogels, which are hierarchical assemblies of -helical protein fibrils that undergo structural changes (e.g. via gel-sol transitions) in response to changes in the environmental temperature. The major benefits of stimuli-responsive protein-based hydrogels include high biocompatibility and potential control over structure and pharmacokinetics, both via sequence. However, only a few protein-based hydrogels have been reported to date, likely due to the inherently large protein design space and limited molecular understanding of stimuli-response. In this SURF, the goal is to create a machine learning classifier trained from existing literature data and data generated from molecular dynamics simulations to predict hydrogel outcomes given sequence. Research in this area will support our long-term goal to computationally design coiled-coil-based hydrogels with tailored drug delivery properties.

Student’s role and learning objectives: 

The student will read through the literature, curate data from coiled-coil databases and literature, train data-driven classifiers, and prepare/run/analyze molecular simulations.

The learning objectives include:
• How to curate data and how to design and train classifiers
• How to prepare, run, and analyze molecular dynamics simulations
• How to use high-performance computing resources and the Linux operating system
• How to manage computational workflows (Git, lab notebooks, scripts, etc.)
• How to code in Python and Bash
• How to critically read the literature
• How to prepare and deliver oral presentations

The student will give brief updates over Slack once a week and have an extended meeting (joint with other group members in the same research area) with the PI every two weeks. The student will also participate in regular biweekly group meetings. The group members and PI will be accessible both in-person and via Slack.

Faculty Mentor: Kevin Cash | Chemical and Biological Engineering

Project Abstract: 

Fluorescent ionophore-based optical nanosensors are a tool for monitoring analyte concentration in biological systems. While not perfectly selective, they do have well understood selectivity for correct vs incorrect analytes. This lets us monitor multiple analytes simultaneously and, with the known interactions between multiple sensors, report out unbiased measurements for ionic concentrations.

Student’s role and learning objectives: 

The student’s role during this SURF fellowship is to develop and test nanosensors for monitoring multiple ionic analytes simultaneously. Pending progress during the fellowship period, the student may also perform preliminary biological imaging experiments to test the nanosensors.

Faculty Mentor: Suzannah Beeler | Chemical and Biological Engineering

Project Abstract: 

A currently under-explored aspect of biology lies in the surprising fact that magnetic fields can perturb living organisms. As just one example, tadpoles grown in the absence of Earth’s magnetic field demonstrate significant developmental abnormalities. These results are quite surprising, and our current understanding of biology fails to explain any role that magnetic fields should play in the realm of living matter. Biological impacts of magnetic fields have been measured in a range of areas, from microbial life to plants and animals.

In this project, we aim to better quantify the impacts of magnetic fields on microbial systems – studying growth, metabolism, and eventually species-species interactions and microbial diversity. Towards that, the student on this project will be developing the tools to monitor growth and metabolism of microbial systems under different static magnetic fields.

Student’s role and learning objectives: 

The student’s role during this SURF fellowship is to develop and test initial magnetic field impacts on cellular growth and metabolism using model microbial organisms grown in the presence of static magnetic fields. By the end of this SURF fellowship, students should be able to reproducibly grow cell cultures on small scale and measure their growth curves in the presence or absence of magnetic fields. Pending student interest, they may also fabricate systems (with 3D printing and rapid prototyping approaches) to control the magnetic field.

Faculty Mentor: Carolyn Koh | Chemical and Biological Engineering

Project Abstract: 

Clathrate hydrates are crystalline solids comprised of hydrogen-bonded water cages that can trap small gas molecules (e.g., CO2). In the presence of saline solution, clathrate hydrate crystals will form, while excluding the salt ions from the water cages, such that separating the clathrate hydrate crystals from the concentrated saline solution can produce fresh water. A key challenge to advance the clathrate hydrate technology for desalination is understanding the interfacial interactions that can control crystal nucleation and growth, which will be the focus of this project.

Student’s role and learning objectives: 

Experimental research skills, interfacial tension measurement methods, crystal growth techniques.

Faculty Mentor: Jose Delgado | Chemical and Biological Engineering

Project Abstract: 

Clathrate hydrates are inclusion compounds that are important in energy/fuel transport and storage. Surface properties, including interfacial tension and particle wettability are key parameters that control these energy applications of gas hydrates. The focus of this project is to measure the water/surfactant interfacial tension over a range of surfactant types and concentrations, and hydrate surface/water contact angles over a range of temperatures. This information is not only important to advancing the energy applications of hydrates, but also to models simulating these interfacial interactions.

Student’s role and learning objectives: 

Student will be performing interfacial measurements (interfacial tension, contact angle) to characterize liquid systems with energy applications. In addition, student will be provided with a strong background on surface chemistry and gas hydrates.
Mentoring activities will be focusing in providing a proper theoretical and practical induction to the student on the experiment work to be performed. Likewise, mentor-student weekly meeting will take place to design experiments, review results and discuss the way forward of the project.

Faculty Mentor: Andrew Herring | Chemical and Biological Engineering

Project Abstract: 

Green Hydrogen is an important energy carrier as the world transitions to a sustainable energy future. Currently the product of hydrogen from water splitting via electrolysis using renewable wind or solar electricity is not cost competitive with the product of hydrogen from steam methane reforming. Anion exchange membranes (AEMs) could enable non-precious metal catalysis and compact load forming water electrolysis that would approach the DOEs earth shot goal of $1 a Kg of H2 by 2030. In this project the student will fabricate high quality AEMs from polymers synthesized in our laboratory, build electrodes, fabricate membrane electrode assemblies, and test them in small bench top electrolysis devices.

Student’s role and learning objectives: 

The student will learn how to process polymers in to membranes with a high level of QA/QC. The films will be tested for water swelling, ion change capacity and ionic conductivity using ex-situ techniques. Standard electrodes will be applied to the membrane to fabricate membrane electrode assemblies. Electrolysis cells will be built, cracterzied for performance and tested for durability.
The student will learn how polymer physics affects the performance of electrochemical devices. The student will learn how the optimization of electrochemical engineering facts device performance.
The student will work daily with Postdoctoral Fellow Dr. Sri Ponnada and Research Associate Ms. Mei-Chen Kuo. The group will meet weekly throughout the summer to guide progress and interpret data and results.

Faculty Mentor: Ramya Kumar | Chemical and Biological Engineering

Project Abstract: 

Antisense oligonucleotides are short single-stranded nucleic acids that modulate gene expression and enjoy a broad therapeutic scope spanning disorders of the central nervous system, ocular diseases, metabolic disorders, and cancer. As more ASOs enter clinical trials or await FDA approval, concerns surrounding prohibitive costs, the invasiveness of ASO delivery procedures such as lumbar punctures and sub-retinal injections, and dose-dependent toxicity have been mounting. Polymers are particularly promising solutions since their interfacial properties can be precisely tuned to protect ASOs from nuclease degradation and obviate the need for extremely high ASO doses. However, unlike double-stranded payloads or bulkier payloads such as mRNA ASOs are not efficiently encapsulated by polymeric vehicles since the physical characteristics of ASOs diverge widely from those of canonical nucleic acid therapies, with the latter possessing a denser hydration layer and much livelier electrokinetic characteristics. Despite abundant evidence-including our preliminary data-that ASOs, particularly those with phosphorodiamidate or morpholino modifications are not sufficiently anionic to participate in polyelectrolyte complexation with cationic nanocarriers, alternative design approaches to promote polymer-ASO association remain elusive.

We have develop polymer-grafted nanoparticles wherein feeble electrostatic driving forces for ASO binding are reinforced by crowding-induced entropic stabilization, thereby pioneering a conceptual shift away from polyelectrolyte complexation. By tuning the polymer chain crowdedness in their corona, we will design HNPs that bind and protect ASOs while yet remaining impervious to degradative enzymes such as nucleases, optimize the spatial arrangement of ASOs within brushes to permit rapid intracellular release while yet retaining resistance against protein displacement and nuclease activity, identify polymer grafting densities wherein protein adsorption is attenuated (Aim 3), and mediate efficient and non-toxic ASO delivery.

Student’s role and learning objectives: 

1. Learn cell culture techniques and perform cell culture/troubleshooting
2. Perform transfection with polymeric carriers, evaluate delivery efficiency, cellular uptake ,toxicity
3. correlate transfection trends with polymer attributes (length, composition, charge)
4. Perform polypelx characterization as needed
5. Acquire proficiency

Faculty Mentor: Amadeu Sum | Chemical and Biological Engineering

Project Abstract: 

Water is ubiquitous, and when combined with gas, water forms clathrate structures, which are a solid mixture of water and gas. While the crystal structure of these clathrate structures are well defined, their morphology in terms of shape, size, and texture can vary widely depending how the clathrate structures are formed depending on temperature, pressure, composition, mixing, surfaces, and so on. The morphology plays a very important role in how water in the form of clathrate are used in energy storage, energy transportation, and energy production. This project explores the diversity of clathrate morphology to catalog their richness and understand their science/engineering through visualization of their morphology..

Student’s role and learning objectives: 

Students need to have a desire to learn and be creative with simple visualization techniques including photo, video, lighting, and image processing.

Regular weekly meetings will be scheduled with the students to develop the project and establish a regular timeline for progression.

Faculty Mentor: Alan Sellinger | Chemistry

Project Abstract: 

Detection of special nuclear materials (SNMs) at borders is imperative for global safety. However, current forms of detection are too expensive to screen all cargo ships, trucks, or trains passing across borders. Plastic scintillators are emerging as a cost-effective form of first-line detection for SNMs. As a first-line of screening, plastic scintillators must be able to discriminate between hazardous materials, like plutonium, and benign ones, such as kitty litter. While kitty litter only emits gamma rays (very small amounts so kitty is safe!), SNMs emit both neutrons and gamma rays. Plastic scintillators can differentiate between benign materials and SNMs by distinguishing between neutrons and gamma rays. One method to distinguish these two types of radiation is called pulse shape discrimination. In Dr. Sellinger’s group, we combine small-molecule organic chemistry, and polymer chemistry with an understanding of nuclear physics and material science. With this interdisciplinary approach, we can design, synthesize, and characterize novel polymers and fluorescent molecules capable of distinguishing between plutonium and kitty litter. Students will have the opportunity to dive into organic synthesis and materials characterization, while learning to collaborate and communicate with nuclear physicists and engineers.

Student’s role and learning objectives: 

The student would learn many new things:
1. organic and polymer synthesis and purification involving air-free conditions using Schlenk glassware, column/flash chromatography, distillations , etc
2. 3-D printing using VAT polymerization of plastic scintillator formulations, develop new solutions for 3-D printing, learn the basic physics of how plastic scintillators work, interact with collaborators at Georgia Tech, Lawrence Livermore and Sandra National Labs, etc
3. use many types of organic/polymer characterization/systems – DSC/TGA (thermal properties), uv/vis and fluorescence spectroscopy, nitrogen 4-arm glove box, microwave reactor, NMR spectroscopy, GC/MS, LC/MS, MALDI-TOF was spectrometry, etc
4. student would be under the daily mentorship of highly qualified graduate students and of course, Prof. Selinger’s door is always open!

Faculty Mentor: Christine Morrison | Chemistry

Project Abstract: 

One way to mitigate the ever-increasing concentration of carbon dioxide in the earth’s atmosphere is to develop carbon recycling catalysts. Such catalysts would capture and convert carbon dioxide waste from fossil fuels into value-added products. This work aims to explore the viability of iron-sulfur clusters as potential carbon recycling catalysts. Iron-sulfur clusters were first discovered in biology, where they are essential to the survival of every species due to their electron transfer and substrate reduction capabilities. These properties are also useful in industrial catalysts. Moreover, iron-sulfur clusters offer some advantages over common inorganic catalysts because they are composed of earth-abundant elements and operate under mild conditions. In this project, the student will create iron-sulfur clusters and characterize their carbon dioxide reduction capabilities.

Student’s role and learning objectives: 

The student will be trained to independently synthesize iron-sulfur clusters in a glove box. The student will also be trained to characterize the material using common synthetic characterization techniques as well as test their carbon dioxide reduction capabilities using gas chromatography. The student will learn these techniques from a graduate student in the Morrison lab. The results of this work will contribute to ongoing projects in the lab and be included in publications; therefore, the student can expect to be an author on at least one manuscript. The student and project trajectory will be supervised by graduate student and Dr. Morrison.

Faculty Mentor: Christine Morrison | Chemistry

Project Abstract: 

This research aims to elucidate the fundamental biochemistry of inhibition and activation of an essential cysteine desulfurase in Staphylococcus aureus using chemical probes. The enzyme, called SufS, catalyzes sulfur acquisition in the sulfur mobilization (SUF) pathway, which is required to assemble essential iron-sulfur (Fe-S) clusters in bacteria. The SUF pathway is one of several pathways of Fe-S cluster biosynthesis, which are evolutionarily conserved throughout the kingdoms of life. Some organisms, including S. aureus, other Gram-positive bacteria, and some parasites, are unique in that they exclusively rely on the SUF pathway because they lack redundant Fe-S cluster machinery. Therefore, the SUF pathway is essential in these organisms. This provides an opportunity to explore how to modulate this pathway in a simpler system and investigate the impacts of modulation on cell survivability and iron homeostasis.

Student’s role and learning objectives: 

The student will work very closely with a graduate student in the Morrison group for learning instrument/technique training, experimental design, and project direction. Specific laboratory techniques include: cell culture, protein purification, in vitro assays, crystallography, computational modeling, and protein characterization. As the student gains experience, they may operate in the lab with greater independence, but they will always be able to access grad students or Dr. Morrison as questions arise. After receiving initial training in key lab techniques and is comfortable in the lab, the student is expected to work on their own independent project that may be published. The student’s experiments and project development will be supervised by the grad student and PI.

Faculty Mentor: Christine Morrison | Chemistry

Project Abstract: 

This research aims to elucidate the fundamental biochemistry of an essential cysteine desulfurase in Staphylococcus aureus. The enzyme, called SufS, catalyzes sulfur acquisition in the sulfur mobilization (SUF) pathway, which is required to assemble essential iron-sulfur (Fe-S) clusters in bacteria. The SUF pathway is important because it is one of several pathways of Fe-S cluster biosynthesis, which are evolutionarily conserved throughout the kingdoms of life. Among the different pathways that biosynthesize Fe-S clusters, the SUF pathway in Gram-positive bacteria (such as S. aureus) is the least understood. In this project, the student will assist in fundamental characterization of SufS from S. aureus, including its kinetics and substrate scope. This work is important because it will provide fundamental information about an essential enzyme and it will lay the foundation for pursuing this enzyme as a drug target for developing new antibacterial agents.

Student’s role and learning objectives: 

The student will work very closely with a graduate student in the Morrison group for learning instrument/technique training, experimental design, and project direction. Specific laboratory techniques include: cell culture, protein purification, in vitro assays, crystallography, computational modeling, and protein characterization. As the student gains experience, they may operate in the lab with greater independence, but they will always be able to access grad students or Dr. Morrison as questions arise. After receiving initial training in key lab techniques and is comfortable in the lab, the student is expected to work on their own independent project that may be published. The student’s experiments and project development will be supervised by the grad student and PI.

Faculty Mentor: Annalise Maughan | Chemistry

Project Abstract: 

Lithium-metal-phosphides represent an understudied group of materials that have the potential to exhibit high ionic conductivity. Li9GaP4 was recently shown to exhibit reasonably high ionic conductivity of 3 mS/cm which could be further improved with the introduction of Li interstitials or Li vacancies. Experimental efforts will be focused on substitution of P3- with S2- and compensating Li+ vacancies. Furthermore, Ga3+ could potentially be substituted with Zn2+ and compensating Li+ interstitials. After synthesis, materials will be characterized by X-ray diffraction to determine phase-purity and electrochemical methods to determine ionic conductivity and stability against Li metal.

Student’s role and learning objectives: 

Students engaged in this project will use solid-state chemical synthesis techniques to prepare known and yet-undiscovered solid-state electrolyte materials. The student will learn how to characterize their new materials through analysis of X-ray diffraction data. The student will be trained to collect their own data on a top-of-the-line X-ray diffractometer and to plot and analyze these data using Python scripting and through the use of dedicated analysis software. The student will also learn electrochemical characterization techniques to determine ionic conductivity and electrochemical stability, which the student will use to determine the utility of their materials for potential battery applications. The student will be mentored by a senior member of the research group with biweekly meetings with the PI and weekly group meetings. The student will also be engaged in some of the professional development activities of the Mines Materials Science NSF REU.

Faculty Mentor: Mike McGuirk | Chemistry

Project Abstract: 

Porous materials have broad industrial applications including catalysis and separations. Their properties are linked to both what they are made of and how that matter is connected to form the material. While most focus goes to thinking about how changing the matter will affect material properties, we focus on how changing connective tissue of porous materials enables unique properties. In this project we will synthesize new molecules capable of form a recently discovered type of molecular interaction called a “halogen bond”. These molecules will be used to assemble crystalline materials, that through molecular design and material growth conditions we hope to achieve porous materials entirely constructed through halogen bonding. In doing so would achieve the first of its kind and bring a new class of materials into the world.

Student’s role and learning objectives: 

The student will be mentored by both the professor and a 3rd year graduate student. We will meet weekly to discuss research. The graduate student will work with the undergraduate student on a daily basis. In the laboratory, the student will be trained in organic and inorganic synthesis, nuclear magnetic resonance spectroscopy, and powder X-ray diffraction. The goal is to train the student to be fully autonomous in the lab. Outside of the lab, the student will be trained in understanding the literature, scientific writing, and effective presentations. Communication is a large emphasis in our research group, therefore the student will be strongly educated in this realm.

Faculty Mentor: Daniel Knauss | Chemistry

Project Abstract: 

The project will synthesize and modify new polymer materials and characterize their potential for application as solid state electrolyte membranes. The materials will be explored as membranes for a variety of energy conversion devices including batteries, fuel cells, and electrolyzers. The student will synthesize new polymers, modify the materials with additives, and characterize using a variety of techniques including chemical analysis methods, materials property evaluation, and characterization of electrical and ionic conductivity.

Student’s role and learning objectives: 

The student will learn and improve organic polymer synthesis techniques, develop skills in a variety of characterization techniques including NMR, FTIR, and UV-Vis spectroscopies, GPC, electrical and ionic conductivity, and materials properties evaluation. The student will develop membrane processing techniques and develop the skills necessary to fully evaluate the materials for application. The professor will mentor the student along with graduate students in the group in synthesis, characterization, planning, and writing with the goal that the student will be prepared for graduate studies research activities by the completion of the summer project.

Faculty Mentor: Brian Trewyn | Chemistry

Project Abstract: 

A major sources of carbon dioxide leading to the climate change effects we are witnessing is the combustion of fossil fuels. Hydrogen energy is a promising alternative to provide clean energy; however, hydrogen is challenging to store and transport. Thus, liquid chemical carriers (e.g. formic acid, ammonia, etc.) have been identified as a liquid organic hydrogen carriers due to the ease of storage and transportation and low toxicity. When combined with a precious metal catalysts, these chemicals decomposes to hydrogen and carbon dioxide for formic acid and hydrogen and nitrogen for ammonia through a dehydrogenation mechanism. We are proposing that alternative energy (e.g. light) can be used to catalyze the dehydrogenation of formic acid and earth abundant metals, alternative to ruthenium, can be used to decompose ammonia.

Student’s role and learning objectives: 

Student will demonstrate how to synthesize metal catalysts supported on porous nanomaterials
Student will evaluate the textural properties of the synthesized materials
Student will demonstrate the ability to measure the catalytic performance of the materials
Student will demonstrate and hone presentation skills in oral form to other graduate students and me.

Mentoring activities will include regular weekly meetings with myself and team of students working on similar projects. Presenting at group meeting a couple times over the summer and mentoring high school students working in the lab.

Faculty Mentor: Lori Tunstall | Civil and Environmental Engineering

Project Abstract: 

Complex surfactant mixtures, called air-entraining agents (AEAs), are used in concrete to purposefully introduce a small volume of tiny, well-dispersed air bubbles into the concrete to protect the concrete against frost damage. Control of the air volume and bubble distribution in concrete is essential–if the bubbles are too large or occupy too large a volume, the concrete will be weakened; however, if the air entrainment is insufficient the concrete will degrade prematurely. Certain chemical additives and supplementary cementitious materials, such as fly ash, have been found to interfere with air entrainment in concrete in unpredictable ways. Recently, our group has proposed a new hypothesis to explain this interference; however, it is unclear how broadly the theory applies since the initial work focused only on two types of fly ashes. This project is focused on testing the hypothesis more broadly, through assessment of multiple fly ashes in collaboration with other university laboratories at The Ohio State and Oklahoma State University.

Student’s role and learning objectives: 

The student’s roles will include measuring AEA adsorption onto fly ash, conducting the foam index test, making concrete samples, and conducting air void image analysis on concrete samples. Training will be provided for all roles.

Before the student begins laboratory research, we will discuss the student’s personal goals and our mutual expectations for summer research. We will work together to develop a plan on how I can best support the student in their goals and expectations. Following, I will give an overview of the background needed to understand the work and give a list of suggested readings if the student is interested in learning more. At the start of laboratory work and after initial training, I will supervise the student in the lab and be available for questions and support. This support will gradually diminish so the student can increase in independence. We will have weekly meetings discussing research progress and questions, in addition to discussing career goals and longer-term interests.

The student learning objectives of this project are: 1) explain how air entrainment helps protect concrete against frost damage; 2) explain how air entraining agents work to stabilize air bubbles within concrete; 3) explain how the novel hypothesis for air loss in concrete with fly ash differs from the previously accepted theory; 4) make high-quality air-entrained concrete; 5) conduct air void image analysis for determining air volume and air void spacing factor; 6) conduct the foam index test; and 6) explain what adsorption is and why it varies with solution concentration.

Faculty Mentor: John Spear | Civil and Environmental Engineering

Project Abstract: 

Microbes live everywhere and on seemingly everything. We are working on a cave system west of Cody, Wyoming, the Shoshone Canyon Conduit Cave, and hope to better understand both the microbes and minerals of this sulfidic cave system. We completed a sampling trip to the cave in mid-March and hope to process samples for mineralogy and microbial community membership over the summer of 2023. The samples will be processed for microbiota by DNA/RNA extraction, PCR and DNA sequencing to tell the story of ‘who is there’ and perhaps, ‘what are they doing.’ The work will serve to better inform on the kinds of organisms found in caves and greater microbial life in general.

Student’s role and learning objectives: 

Student will process cave samples for mineralogy and microbiology. This will involve learning things like x-ray diffraction (XRD) for mineral composition; DNA/RNA extraction from collected and frozen samples; polymerase chain reaction (PCR); DNA sequencing preparation; and bioinformatic interpretation of generated DNA sequence working with a graduate student.
Learning objectives would be:
— Learn
— Mineralogy techniques (XRD)
— Microbiology techniques (Microscopy, PCR, DNA/RNA extraction, bioinformatics)
I will meet with student multiple times in person per week to get started, and if away, via Zoom. SURF student will work with another student funded by the project as well as oversight by a graduate student who will be present in the lab.

Faculty Mentor: Timothy Strathmann | Civil and Environmental Engineering

Project Abstract: 

This project will examine the underlying mechanisms responsible for the destruction of halogenated organic water pollutants subjected to hydrothermal alkaline treatment (HALT), a new technology recently patented by Mines that is being used to treat water contaminated by highly persistent pollutants, including solvents, surfactants, pesticides, and flame suppressants. While the technology has been demonstrated to be effective, we still have questions about the underlying principles and mechanisms, which this project will examine.

Student’s role and learning objectives: 

The student will work with the team to examine the mechanisms, running batch reactions at varying reaction conditions, and analyzing the residual concentrations of contaminants in the water following treatment to determine reaction rates for various structures. The student will model the rates of reactions and work with graduate students to identify potential transformation products using mass spectrometry methods. The student will meet regularly with the mentor to discuss progress and plan the next experiments.

Faculty Mentor: Qi Han | Computer Science

Project Abstract: 

This project is to research multi-user mobile augmented reality. Topics to be studied include the current multi-user architecture, multi-user communications, and technologies used to enable augmented reality, including but not limited to visual-inertial Simultaneous Localization and Mapping (SLAM). The state-of-the-art research issues in the field, such as limitations imposed by computation, latency, energy/battery utilization, and storage availability, will also be explored. The focus will be on developing algorithms and software that will enable a proper multi-user augmented reality experience with the limited resources available on the phone.

Student’s role and learning objectives: 

The student will read the provided research papers, and design a project on an Android device to facilitate user experience using the knowledge derived from the multi-user setting.

After completing the project, the student will write a report describing the problem tackled, the solutions, and the experimental results.

The student will be working with a Ph.D. student closely and meeting with the faculty advisor weekly to discuss problems, plans, and progresses.

Faculty Mentor: Hua Wang | Computer Science

Project Abstract: 

Cancer develops in disease tissues, which is the most severe disease diagnosed in the United States of America. Given that an early diagnosis is imperative to prevent cancer progression, many machine learning models have been developed to automate the histopathological classification of the different types of carcinomas in recent years. In this study, we how to classify the histopathological cancer images and determine which tissue segments in an image exhibit an indication of using large-scale histopathological images, where we mainly address the computational efficiency of designed machine learning models.

Student’s role and learning objectives: 

The research objective of this project is to address the computational challenges in an innovative big data application on medical image computing. This project will study the problem of integrating multi-level data with the emerging key computational techniques: large-scale non-convex sparse learning models with linear convergence algorithms and linear computational cost multi-task multi-dimensional data integration algorithms.

1. The students will learn the skills to perform data processing and management.
2. The students will be involved in my research team to perform research on machine learning and data mining.
3. The students will be involved in scientific paper writing for the results of this project.
4. The students will have a chance to work together with my collaborators in medical schools.
5. The students will gain fundamental knowledge of medical image computing, as well as how to use machine learning, as well as computational algorithms, to deal with problems in medical image computing. In a word, after the training in this project by successfully completing the assigned research tasks, the student is expected to be ready to pursue a graduate degree in machine learning, data mining, artificial intelligence, or a broader area of computer science.

Faculty Mentor: Neil Dantam | Computer Science

Project Abstract: 

Robots require novel reasoning systems to achieve complex objectives in new environments. Everyday activities in the physical world couple discrete and continuous reasoning. For example, setting a dinner table requires a robot to make discrete decisions about which objects to pick and the order in which to do so, and execute these decisions by computing continuous motions to reach objects or desired locations. Robotics has traditionally treated these issues in isolation. Reasoning about discrete events is referred to as task planning while reasoning about and computing continuous motions is the realm of motion planning. However, several recent works have shown that separating task planning from motion planning—that is finding first a series of actions that will later be executed through continuous motion—is problematic; for example, the next discrete action may specify picking an object, but there may be no continuous motion for the robot to bring its hand to a configuration that can actually grasp the object to pick it up. Instead, Task-Motion Planning (TMP) tightly couples task planning and motion planning, producing a sequence of steps that can actually be executed by a real robot to bring the world from an initial to a final state. We will investigate various approach and algorithms for robots to perform this type of real-world planning.

Student’s role and learning objectives: 

Student role: Student will be responsible for the design, implementation, and/or testing of robot planning algorithms and software. Experiments using physical robots (ground robots or robot arms) are a possibility.

Student learning objectives: Student will develop an understanding of robot programming, task planning, and robot motion planning techniques and libraries. Student will learn various methods and algorithms for search and optimization in complex spaces.

Mentoring: Weekly individual meetings with the student and faculty mentor to discuss progress and provide directed guidance. Weekly lab meetings to discuss the overall project and integration. Assigned graduate student mentor for the student.

Faculty Mentor: Tom Williams | Computer Science

Project Abstract: 

For autonomous agents such as robots to communicate with humans naturally and efficiently, they must be able to refer to different entities using concise referring forms, such as it, this, or that N. Previously, we have collected a dataset and proposed computational models using textual data. However, gestures can be informative as well. For example, pointing at an object directly informs the use of it. In this project, the student will work on the gesturing feature to make the existing computational model more accurate with not only speech data but also gesturing information.

Student’s role and learning objectives: 

The undergraduate student will work with Prof. Tom Williams and postdoc Dr. Zhao Han to code the gesturing data and re-train the model using the state-of-art explainable machine learning techniques, such as decision tree. For mentoring, the student will meet Dr. Han or Dr. Williams weekly or more often depending on the student’s progress. A mentor-mentee contract will be developed to achieve the project goal and the student’s personal goal as well as lay out expectations and support from mentors.

Faculty Mentor: Chuan Yue | Computer Science

Project Abstract: 

A variety of web-based attacks such as phishing, cross-site scripting, and drive-by download have been continuously causing severe damages to users and organizations for over two decades. It is very challenging to effectively defend against them especially because they continuously evolve and adapt to the countermeasures. In this project, we design systems, algorithms, and user studies to secure the web by taking the policy analysis and improvement approach. This project is a part of a larger ongoing project. Strong web programming background is needed for the student who would like to work on this project.

Student’s role and learning objectives: 

The student will work with Dr. Yue and his PhD students to measure and analyze new security risks on the web.
The student will be trained with research methodology as well as system design principles and skills.
The student will (1) read and present research papers, (2) discuss research ideas, (3) discuss the design of the study,
and (4) conduct the student with the team.
The student is expected to attend (can be online) the weekly project meeting.

Faculty Mentor: Katharina Pfaff | Geology and Geological Engineering

Project Abstract: 

Diamond drill core and drill cuttings represent the most important sources of subsurface geological information in the minerals and geothermal industries. Large amounts of drilling are typically conducted as projects in the minerals and geothermal industries advance from the early exploration to the production stage. Continuous XRF scanning on core and hyperspectral core scanning are newly developed method available at Mines which will allow the successful SURF student(s) to obtain images and topography data as well as co-registered geochemical information. These co-registered datasets will be augmented with detailed mineralogical information acquired in the Mineral and Materials Characterization Facility in the Department of Geology and Geological Engineering. The aim of this project is to advance our knowledge of the subsurface at the Coso geothermal field in California to advance the use of geothermal energy resources.

Student’s role and learning objectives: 

The selected SURF student(s) will be closely working with PIs Pfaff and Monecke and graduate student assistants. The student(s) will participate in research group meetings and meetings with university and industry stakeholders. The student will be trained in sample preparation, data acquisition, data interpretation, and subsurface modeling. The student(s) will participate in discussions and present their findings to their mentors.
The research project will be subdivided into three general milestones with discrete goals:
(I) Learning: Working in an analytical laboratory (including safety training), sample preparation, data acquisition, quality control, organizational skills, and literature review
(II) Learning/Analysis: Achievement of information literacy, data analysis, critical thinking, training of effective communication skills, data acquisition and interpretation
(III)Analysis/Synthesis/Presentation: Data interpretation, critical thinking during data analysis and quantitative reasoning skills, data presentation – quantitative and scientific reasoning, effective communication skills and presentation of research outcomes.

Faculty Mentor: Piret Plink-Bjorklund | Applied Mathematics and Statistics

Project Abstract: 

As the world warms due to rising greenhouse gas concentrations, the Earth system moves toward a climate state without societal precedent, raising the need for studies of past global warming events, where Earth’s history provides a series of natural experiments — actual realizations of how the Earth system responds to greenhouse forcing. Some unmitigated scenarios of greenhouse gas emissions (RCP8.5) predict climates like those of the Early Eocene by 2150. Although the unmitigated scenarios may not be the most likely to transpire, this establishes the Early Eocene as an important end-member climate analogue or test bed.

This project studies the extremely warm Early Eocene climates and how ancient rivers responded to these climate changes. Ancient climate conditions cannot be directly measured, and are rather inferred from proxy data. Proxies are not direct indicators for changes in temperature, precipitation or evaporation, but rather provide indirect evidence for how temperature and hydrological changes impacted the Earth surface or biota. In this project, we will collect such proxy data for Early Eocene atmospheric drivers, temperature and precipitation to reconstruct multiple consecutive global warming events. We will also collect data on how rivers and their flood characteristics and floodplain ecosystems responded to these climate changes.

Student’s role and learning objectives: 

We are looking for two undergraduate students who will work on different aspects of this project, where each closely collaborates with a PhD student. One of the students will focus on atmospheric driver, temperature and precipitation proxy data collection and reconstruction, and the other student on river flood and floodplain ecosystem proxy data collection and reconstruction.

Both students will learn how to set up and conduct research projects, including scientific questions and testable hypothesis, how to plan and conduct work that ensures results, and how to disseminate the results by conference presentations or publications. The students will learn about past climate changes and how the past proxy data can inform our future. Both students will learn field data collection and laboratory sample preparation and analyses. Field work component will be important so both students need to be interested in hiking, scrambling and spending time outdoors. Both students will also learn statistical and machine-learning techniques of data analyses.

The students will work closely with PhD students in the field and laboratory. We will together develop a research plan and decide on expected outcomes. We will encourage the student to present at the department’s yearly science fair as well as at a major conference, and to co-author a publication if appropriate.

Faculty Mentor: Danica Roth | Geology and Geological Engineering

Project Abstract: 

For over a century, Mima Mounds of the Puget Lowland have baffled geologic thought. Numbering in the thousands along proglacial terraces, these elongated dome-like ellipsoids measuring up to 2 m in height fuel both speculation and controversy (Washburn, 1988). With similar “Mimalike” mounds across the US and beyond, a variety of genetic models have been proposed ranging from biotic to seismic. Nonetheless, the shared or discrepant origins of these discrete mound fields remains unresolved, fueling debate along lines of disciplinary and regional bias (Pope, 2021c). Even classification of mound fields appears elusive, yet many Mimalike mound fields appear to be associated with Pleistocene terraces (Pope, 2021b). This raises the question: do terraces represent sites for preservation of mounds or do they play some causal role in the formation of Mimalike mounds? Considering these observations, the proposed study purposes to test the observations of Pope (2021b) to determine the strength of correlating mounds to host terraces and the specific genetic, morphological, and chronostratigraphical relation the mounds of the Puget Lowland hold to their host terraces, thereby constraining the mounds’ origin.

Student’s role and learning objectives: 

Following literature review to more robustly assess the association of Mimalike mounds and terraces, GIS mapping will analyze the spatial correlation between the mounds to their host feature, paying heed to indications of constraint by the terrace versus preservation bias along terraces. Meanwhile, the sedimentological association of the mounds and the terraces will be queried through coring the cardinal points of three mounds using PVC piping to collect the cores, similar to Seifert et al. (2009) in the Oklahoma mound fields. Once retrieved, grain size analysis will “map” the distribution of grain sizes throughout the mounds and related to terrace-scale trends (e.g., gradient) using GIS. Examination of the provenance of pebbles within the mounds, as begun by Pope et al. (2020), will be continued first with hand samples to evaluate the composition of the pebbles to narrow the provenance, and thus origin, of the mound diamicton itself. Analysis of grain size, mineralogy, and clast petrology could begin with initial examination in Summer 2023 but may not fully mature until Fall 2023.

Student will have weekly to biweekly meetings to discuss progress, challenges and questions, as well as email, Slack and drop-in availability. The student will also be included in weekly lab group meetings, and will be invited to attend lab journal reading groups, which will provide exposure to a collegial research environment and provide networking and professional development opportunities. Depending on student interests, goals and performance, this project may also lead to student co-authorship on scientific publications and presentation at scientific conferences, and additional research, internship and teaching or field assistantship opportunities with the group going forward.

Faculty Mentor: Brandon Dugan | Geophysics

Project Abstract: 

The Tuaheni Landslide Complex is a seafloor feature located off the north island of New Zealand that records the migration of a submarine landslide. Previous research has suggested that this landslide has moved via slow, viscous like processes. Other studies, however, have suggested that high water pressures may have created rapid, infrequent movement of the landslide material. In this project, we will look into more detail of the geotechnical and hydrogeological properties including sediment permeability and strength to better understand which of these mechanisms – continuous, slow movement or rapid, infrequent rapid movement – are more plausible. These properties will be integrated into numerical models that simulate the landslide initiation process which will be validated against the observations. These models can also be used to estimate under which conditions a large, rapid landslide could occur. It is critical to understand the potential for large, rapid landslides in ocean basins as they can create tsunamis that result severe economic impacts, public health hazards, and loss of life.

Student’s role and learning objectives: 

The undergraduate student will be responsible for integration of existing data into established data analyses and modeling programs so a modest amount of data and computer/coding proficiency is desired. When working with the existing data, the student will be responsible for basic regressions and plotting of the data. In addition the student will do some literature exploration to understand the broader context of this focussed study – the why-is-this-important question. On the mentoring side, I will work with the student to ensure they understand the types of data they are analyzing, how those data are collected and generated, and how the modeling programs work. I will also help the student develop strategies for literature research and keeping notes on research progress. For the larger research experience, I will provide the student with an overview of how research funding works from idea generation to proposal writing to doing the research to providing project deliverables and research papers. The student and I will have weekly meetings where we will assess accomplishments since the previous meeting, discuss questions the student has, and set mutually agreed-upon goals for the next meeting.

Faculty Mentor: Eileen Martin | Geophysics

Project Abstract: 

Underground mining provides essential materials, but it requires careful planning and monitoring to ensure a safe working environment for the people working underground. In particular, longwall mining involves small, planned rock collapses as part of the mining process. Being able to accurately detect and locate these small rock collapses and the associated small earthquakes can help mine engineers confirm whether the mining process is working as expected, and to inform future mine planning for safe operations. We have used a new technique, called fiber optic distributed acoustic sensing, to repurpose a fiber optic cable that we installed underground as an array of many seismic sensors. We collected over 20 terabytes of data, which are giving us an unprecedented look into the workings of the mine including vibrations due to machinery, as well as small rock collapses and small earthquakes. While we have already done some initial investigations of a collection of earthquakes and a variety of machinery noises in the mine, we need to build a stronger understanding of how much certainty we have in our earthquake detections. Additionally, we need to investigate how much machine learning and signal processing tools can improve the reliability of our earthquake detections, or help us detect more events than we could see previously.

Student’s role and learning objectives: 

Student tasks in this role:
– Detect seismic events with and without denoising approaches applied
– Quantify significance of detected seismic events
– Participate in weekly mentoring meetings and provide updates in monthly check-ins with collaborators at another university, a company and a government agency
– (If remaining time in summer) Investigate uncertainty when only portions of the sensor array are analyzed

Learning objectives:
– Learn about the causes and effects of seismicity in mining
– Learn to quantify the significance/reliability of seismic event detections
– Learn to apply machine learning and signal processing to understand large-scale seismic data
-Learn to improve your science communication and interdisciplinary collaboration skills

To succeed in this project on this short time scale, the student should already: (I) have completed a course using Python for data analysis/visualization or have equivalent experience, and (II) have seen the 1D Fourier transform previously.

The student working on this project will participate in an onboarding day with the project mentor, will meet twice per week the the faculty mentor, and will meet at least monthly with collaborators and industry/government mentors. The student will receive mentorship on presenting their work, designing a poster, and will have the opportunity to present their research as a poster to industry and government mentors in the fall. In addition to discussions of the research and presentation skills, the project mentor will also discuss career paths and graduate school opportunities with the student.

Faculty Mentor: Jeffrey Shragge | Geophysics

Project Abstract: 

The Slumgullion slide is a slow moving earthflow that created the natural earth dam that led to the formation of Lake San Cristobal near Lake City, CO. Lake formation and drainage evolution on the slide’s post-emplacement topography resulted in the deposition of a classic example of a wave-dominated delta. The impressive slide feature was declared a National Natural Landmark, and also provides an excellent natural laboratory to study the interplay of climate, vegetation, wave dynamics, and delta evolution. A detailed geophysical and geological investigation of the slide can inform assessments of the future stability of the slide deposit, which is moving slowly but could mobilize catastrophically. Although the slide itself has been the focus of many studies, the San Cristobal wave-dominated delta that formed in response to the slide events has not been studied, but may contain a compact record of the landscape response to the slide. The delta should be examined because it reflects lake growth, the disequilibrium of the landscape, and the geologic processes working to establish a stable equilibrium profile at a new base level.

Student’s role and learning objectives: 

Role: The student will undertake the following research activities: assist with geophysical and geological survey planning activities; spend approximately 5 days at the Slumguillion Slide site performing geophysical, geological, and geotechnical fieldwork with the investigation team; and undertake data analysis, integration and interpretation activities. Supervision of activities will be conducted by Geophysics Faculty member Jeffrey Shragge and Research Associate Aaron Girard, with contributions from other team members.

Learning Objectives: The student will gain knowledge on geophysical and geological survey design as well as data acquisition, processing, interpretation and acquisition. Students may also gain skills on earth flow mechanics, delta formation, stream and lake hydrology, and laboratory geotechnical experiments. The student will get an opportunity to use structure from motion analysis to understand active processes in the lake created by the slide, and will also gain experience working across the boundaries of multiple fields.

Mentoring: We will have a multi-level mentoring approach in the research group that will include faculty, research associates, and graduate students. The research group will have meetings every other week to discuss research progress. The project team will give feedback to students on their presentations. Students will also have additional, individual meetings with one of the faculty/research associate leads for more focused discussion. If desired, the student can also contribute to grant proposal writing to advance this project and thus will receive mentoring on scientific writing and project development.

Faculty Mentor: Bia Villas Boas | Geophysics

Project Abstract: 

Ray tracing is a powerful technique used in computer graphics and scientific simulations to model the propagation of waves. When it comes to ocean surface gravity waves, ray tracing can provide valuable insights into wave propagation, including their interaction with ocean currents and the seafloor. Such insights are crucial for better understanding ocean wave physics and their role in climate, as waves are a major player in heat transfer and the exchange of gases between the ocean and the atmosphere.

The goal of this SURF project is to develop a Rust-based package that can perform ray-tracing simulations of ocean surface waves. The package will use state-of-the-art numerical algorithms and data structures to efficiently simulate the propagation of waves in complex ocean environments, such as those with varying bathymetry and currents. The package will also include tools for visualization and analysis of the simulation results, allowing researchers to gain insights into the behavior of ocean surface waves in different conditions.

Why Rust? Rust is a modern programming language that combines the performance and low-level control of C/C++ with the safety and memory management features of modern languages like Java and Python. Rust’s unique ownership and borrowing system allows for safe and efficient memory management, making it an ideal language for high-performance scientific computing applications.

Student’s role and learning objectives: 

This SURF project will be carried out in collaboration with Scientists at Scripps Institution of Oceanography, at UC San Diego. The student will work with the faculty mentor and Scripps collaborators to develop an open-source Rust-based package for ray-tracing of ocean surface waves. By the end of the project, the student will have:

– Developed coding skills in the Rust language
– Gained experience in best practices of scientific computing and software development, including version control, packaging, unit testing, and documentation.
– Develop knowledge of physical oceanography and the kinematics of ocean waves.
– Practice collaborative software development and project management through GitHub

The student will be mentored by the Mines faculty mentor and the Scripps collaborators through weekly meetings and group discussions, where guidance and feedback on the project will be provided. Depending on the student’s progress and interest, there is the potential for submitting the results of this project for publication in the Journal of Open Source Software (JOSS).

Required experience: To succeed in this project on this short time scale, the student should have experience with some programming language. Previous experience with Rust is not necessary (although it’s a plus) but the student should be motivated to learn a low-level language and apply computing skills to a scientific problem.

Faculty Mentor: Kathleen Hancock| Humanities, Arts and Social Sciences

Project Abstract: 

In the United States, solar and wind prices at utility scale and distributed levels have been rapidly falling over the last decade. As a result, theories and empirical research that assumes renewable energy sources for electricity cannot compete with fossil fuels (natural gas and coal) without subsidies are now outdated. In addition, old coalitions that once propelled or tried to hold back renewable energy are being upended. It is now a myth that Republican states don’t support renewable energy: Texas, a solidly Republican state, is the leader in wind production and about to become the leader in solar production. Similarly, some Democratic states are laggards. We’ve identified a new category of political player: energy intensive businesses beyond the traditional heavy industry ones (such as steel plants). These include data processing centers, marijuana growers, and cryptocurrency companies. We’ve also found that environmental organizations that once were united in pushing for RE are now sometimes splintering over RE projects that harm wildlife. Finally, we have found social justice groups have joined pro-RE coalitions. We are studying how these groups engage with the RE coalitions.

Mines undergraduates have been working on this project, especially on the EIBs. We now need help collecting and analyzing the literature already out there that discusses renewable energy coalitions in the US and Europe.

Student’s role and learning objectives: 

I will meet weekly with the student to discuss the progress and next steps.

We will discuss how to do a literature review, making clear the difference between peer-reviewed literature and other literature, and I will show the student how to use the databases in our library. We will also cover book searches. Depending on how far we get in collecting the literature, we will start analyzing the documents, writing up what others have found when looking at renewable energy coalitions in the US and some other democracies. The student will read articles and books and summarize the general arguments, comparing and contrasting them. In the process, the student will learn about some political science theories and frameworks.

The findings will be used in a book which will be completed in a 9-12 months. If interested, I will work with the student on submitting the literature review as a separate publication in an academic journal.

Faculty Mentor: Andrew Petruska| Mechanical Engineering

Project Abstract: 

Mines has been awarded a $2M contract from NASA to develop the technology necessary to prepare a landing site on the moon to support the Artemis mission to return astronauts to the surface of the moon. This project is a collaboration between Mines (ME, CS, Mining, Space Resources), Missouri S&T, Bechtel, and Lunar Outpost. At this point in the project we have developed a design concept for the robotic system, have tested subsystems, and are beginning to integrate the full system for functional testing. As this project aims to develop an autonomous site preparation robot that can autonomously clear, grade, and compact a region of the moon, this project spans multiple disciplines including: civil engineering, mechanical engineering, electrical engineering, computer science, and space resources. Students involved will need to work between disciplines and communicate with experts in different disciplines to find the collective optimal solutions to this challenge. Over the summer, a large test bed will be constructed for our 40ft x 40ft preparation area. In the fall and spring semesters of 2023-4, full system testing will begin and will lead to revision in the mechanical design and computer algorithms. Student support of the test bed design, robot integration both hardware and software, test design, performance assessments, iteration on the mechanical and software components is available.

Student’s role and learning objectives: 

The students will join a 10+ person core team. They will contribute to the multi-institution group-wide meetings as well as smaller focused challenge teams. In these challenge teams, they will be pared with a professor and graduate student as well as other undergraduates to achieve a specific goal, such as tuning the controls algorithms or implementing visual rock detection for navigation and planning. These small teams will form and disband as the challenges are overcome, creating a dynamic and agile design environment.

Faculty Mentor: Neal Sullivan | Mechanical Engineering

Project Abstract: 

We are developing new materials for production of hydrogen from water using high-temperature electrolysis. In this project, students will work as members of our research team to fabricate and characterize the performance of high-temperature electrolyzers for hydrogen production and energy storage. Activities will include electrolyzer fabrication, microstructural analysis through electron microscopy, and performance characterization using experimental tools.

Student’s role and learning objectives: 

Researchers at the Colorado Fuel Cell Center are actively developing new materials and devices to drive electricity for making chemicals, starting with hydrogen. We need researchers to help us in this endeavor. The researcher would learn about our device-fabrication process, and analysis techniques needed to evaluate device characteristics and performance. The researcher will work directly with graduate students and research faculty.

Faculty Mentor: Neal Sullivan | Mechanical Engineering

Project Abstract: 

The Colorado Fuel Cell Center (CFCC) seeks a student with skills in data science for helping us characterize the performance of commercial methane sensors. The CFCC is currently working with BPX Energy to quantify the impacts of operating temperature and relative humidity on the response of commercial methane sensors. Large data sets have been assembled through a series of physical experiments executed in the CFCC. In this SURF project, the student researcher will mine these data sets to develop a predictor of methane concentration based on sensor output, including confidence intervals.

Student’s role and learning objectives: 

The student researcher will work within an existing research team at the Colorado Fuel Cell Center to understand our research approach, and the data we are creating. The student researcher will then post-process the large data sets we are developing, and provide a regression fit to these data sets to be used by BPX field operations.

Faculty Mentor: Joy Gockel | Mechanical Engineering

Project Abstract: 

In additive manufacturing, the material is built at the same time as the part. So, the way the part is built impacts the mechanical properties of the material. This project will perform tensile testing of metallic material that was built using the laser powder bed fusion additive manufacturing process. The parameters such as processing conditions (e.g.- laser power, speed, layer thickness, etc.) and machine effects (e.g.- location on build plate) will be related to the tensile properties. The results from this project will help inform the application of additive manufacturing in industries such as medical and aerospace.

Student’s role and learning objectives: 

The student will perform the mechanical tensile tests for the project and data analysis. The student will also learn about the additive manufacturing process and what will affect the tensile properties. Weekly meetings will be scheduled with the faculty and the student to discuss research progress and plans. The participating student will attend the biweekly group meetings to discuss with other students performing research. The student will also be invited to attend the ADAPT quarterly meetings (both summer and fall), with an opportunity to present research and interact with industry members.

Faculty Mentor: Megan Holtz | Metallurgical and Materials Engineering

Project Abstract:

In Hill Hall 302, we will be setting up a new molecular beam epitaxy thin film deposition system to grow designer oxide materials, where we can choose what material to grow atomic layer by layer. Before the system arrives, there is a lot to do: we need substrate materials that have perfect crystal facets which are perfectly clean. The surface of various substrate materials will be tuned by rinsing, etching, and annealing, and then verified using characterization tools such as atomic force microscopy. Once the system is fully set up, the excitement will begin as we are able to see how the system works by growing and characterizing new material systems. In this project, you will learn about thin film deposition, oxide materials, surface chemistry, and materials characterization (such as x-ray and electron diffraction techniques and various microscopies). Get in on the ground floor of an exciting materials engineering lab, and gain experimental skills that will be valuable as you launch your career. People who enjoy and/or want to learn hands-on work, who are in the early stages of undergrad, and/or who are women, minorities, or otherwise underrepresented are encouraged to participate.

Student’s role and learning objectives: 

Tuning surface chemistry by wet methods and by using a furnace, materials characterization such as x-ray diffraction, atomic force microscopy, and electron diffraction. Thin film deposition techniques and characterization methods. Hands-on lab experience with a variety of materials engineering systems including vacuum systems.
Mentoring will be with the PI 1-2 times a week.

Faculty Mentor: Megan Holtz | Metallurgical and Materials Engineering

Project Abstract: 

Strain plays a critical role in all realms of solid-state materials technology, from batteries to semiconductors to metals. Full three-dimensional strain profiles around simple strained objects such as dislocations and at interfaces have been simulated, but never fully characterized on atomic length scales. This proposed work will develop methods to use scanning nanobeam electron diffraction algorithms for three-dimensional data reconstructions to map strain in three dimensions for various nanostructures. The work to develop these algorithms in MATLAB in this project will lead to the development and validation of a general technique to enable 3d strain mapping of many materials.

Student’s role and learning objectives: 

The student will (1) learn MATLAB, (2) simulate data, (3) develop matlab algorithms to process the data into three dimensional datasets. We will meet 1-2 times a week to work on the matlab code together.

Faculty Mentor: Parisa Bazazi | Petroleum Engineering

Project Abstract: 

Microbial activity can affect the efficiency of underground gas storage. Specifically, microbes can consume hydrogen as a source of energy. This results in an overall reduction in the amount of stored hydrogen and may also create acids that can corrode storage materials. To ensure the safety and long-term performance of underground hydrogen storage systems, microbial activity must be considered in their design and operation. For the assessment, the original reservoir fluid and rock samples should be used for the chemical and microbial analysis. Currently, polymerase chain reaction (PCR) techniques are used to analyze reservoir samples and find metabolically functional groups. Alternative approaches are necessary in light of the difficulties in high quality DNA extraction from microbial samples, the presence of PCR inhibitors, and the cost and time of the analysis.
Interfacial energy measurement techniques are considered as an effective tool to quantify the properties of reservoir rock and fluid in an oil production process. Microorganisms are surface-active. Consequently, the presence, type, and concentration of microbes affect the magnitude of fluid-fluid-rock and fluid-fluid surface energies. Interfacial energy measurement techniques are not sensitive to small concentrations of microbes, as they may be influenced by other fluid impurities, and the type of microbe. To enhance the sensitivity of conventional interfacial energy measurement techniques for microbial activity, early-time dynamics of fluid-fluid (EDF) and fluid-fluid-solid (EDS) interfaces are investigated using a coupled side-bottom view imaging system. This platform can quantify the microbial activity within one second.

Student’s role and learning objectives: 

Learning Objectives:
1. Learning the concept of the porous media and the challenges of the underground gas storage
2. Getting familiar with lab environment/lab safety
3. Learning how to culture the bacteria in the lab
4. Learning the layer-by-layer (LBL) surface coating technique
5. Getting familiar with the interracial energy measurement techniques such as drop shape analyzer, surface rheology
6. Learning how to work and communicate in a research group
7. Developing scientific writing and professional presentation skills

Students role:
The student will work directly with the faculty and graduate students in the lab in all aspects of the project from brainstorming to writing the research paper. Specifically this student will be focused on measuring the surface energy of the solid surfaces (glass or rock) before and after the exposure to the hydrogen. The student will analyze and discuss the results accordingly.

Faculty Mentor: Meenakshi Singh | Physics

Project Abstract: 

Crystalline allotropes of silicon, alternative crystal structures to diamond silicon, hold the promise of exciting optical and electronic properties in a silicon-based material. Exotic open caged and open channel structures which can be stabilized at room temperature and atmospheric pressure have been fabricated previously for various applications. However, due to fabrication challenges, their electronics properties and integration into devices has not been fully explored. The central hypothesis of this project is that interstitial impurities/dopants which sit inside the crystalline silicon cages/channels can mitigate key issues in diamond silicon for revolutionary quantum information science materials. The specific experiments for this SURF project will be focused on fabricating and characterizing electronic devices with a view towards quantum information applications. These will tie into the bigger project where characterization of relaxation and coherence times of the dopants using electron spin resonance is being carried out by a graduate student.

Student’s role and learning objectives: 

The student will acquire expertise in nanofabrication and cryogenic electronic measurements. They will also broadly learn about electronic transport, spin dynamics, and qubit properties. I will meet with the student once or twice a week to review progress. In addition, the student will work closely with a graduate student and frequently talk with other professors who are collaborators on this project.