Project Descriptions for the 2026 REU Program

Faculty mentor: Prof. Xinqiao Jia
Materials Science & Engineering, Biomedical Engineering ● 🔗 Research Group Site
Graduate student mentor: Samiksha Udan

Peptides capable of forming homotetrameric coiled-coil bundles will be utilized as the monomeric building blocks (“bundlemers”, BNL) to synthesize protein-like hybrid polymers consisting of covalently linked coiled-coil microdomains with regularly spaced elastin-like peptides (ELP) repeats via step-growth polymerization employing the highly efficient, bioorthogonal tetrazine (Tz) ligation with trans-cyclooctene (TCO). The composition of the ELP and the BNL segments and the polymerization condition will be adjusted to produce a copolymer (ELP-BNL)n that exhibits temperature-induced transition from a rigid rod to a flexible chain through coordinated coacervation of the ELP segments. To demonstrate stimuli-induced molecular actuation, a scrambled BNL peptide (sBNL) unable to assemble into a coiled-coil will be equipped with tetrazine and coumarin (CM) groups at the N- and C-termini, respectively. Inclusion of Tz-sBNL-CM in the polymerization media will afford a CM-functionalized telechelic polymer that can be immobilized on a CM-functionalized substrate at the chain ends through UV light-induced dimerization of CM. Molecular actuation will be achieved through temperature oscillation in combination with light-induced bond formation (< 260 nm) and bond cleavage (> 300 nm). The fluorescence bead will be conjugated to the polymer backbone to enable the characterization of molecular motion through particle tracking microrheology.

Faculty mentor: Prof. Christian Pester
Materials Science & Engineering ● 🔗 Research Group Page
Graduate student mentor: Brock Hunter

Drugs, bacteria, and dyes present in water from commercial and residential waste streams present constant threats to human health which can be addressed through photocatalysis. The design of both scalable photocatalytic materials and photoreactors is paramount to industrial implementation. Our group has previously developed photoactive polymer coatings on glass beads which successfully treated bacteria under blue light. This project focuses on exploring polymeric photoactive beads for implementation into water purification flow systems. Students will focus primarily on suspension and bulk polymerizations and explore topics such as reactor packing optimization, photon upconversion, and bead architecture design. Students will utilize a wide suite of techniques including organic photocatalyst synthesis, various forms of free radical polymerization, microscopy, gel permeation chromatography, ellipsometry, X-ray photoelectron spectroscopy, NMR, UV-Visible spectroscopy, kinetics testing, and flow system design. Working at the interface of materials design, engineering and chemistry; well defined engineering goals will drive students to develop their chemistry knowledge and research intuition to solve the challenges of this project. Students will work with senior researchers of varied backgrounds but similar goals to challenge each other and transform students into excited, discerning leaders of their future fields.

Faculty mentor: Prof. Christian Pester
Materials Science & Engineering ● 🔗 Research Group Page
Graduate student mentor: Ruhao Li

Cool organic syntheses very often conceal a cascade of workup as the dark side—many of which are tedious, and the undisputed champion of hated steps is column chromatography. This project aims to explore a universal strategy that confines the reaction to high-surface-area nanoparticles for significantly simplified workup. To release the target compound, the nanoparticles can be removed to cleave the surface-bound ligands. In the entire process, separation and purification that would otherwise require day-long column chromatography could be replaced by minute-long centrifugation. Imagine doing real synthesis but with the cleanup workflow of instant noodles. Students participating in this project will utilize a repertoire of skills including general organic synthesis, nanoparticle handling, surface tethering and release design, and characterizing products using NMR, FTIR, XPS, etc. No experience is required, but we would like to see motivated and ambitious candidates.

Faculty mentor: Prof. Branislav Nikolić
Physics & Astronomy ● 🔗 Faculty Page
Graduate student mentor: TBD

Magnet is driven out of equilibrium can display fundamental physical phenomena, as well as be a resource for applications. For example, two noncollinear textures could annihilate, thereby offering table-top experimental probe of phenomena predicted to occur on cosmological scale. One could also replicate black hole horizon with proper geometry of magnets. Either of these systems could also be used as a resource for the envisaged magnonics technologies. In this project, student will perform computer simulations of such phenomena using micromagnetics codes. Familiarity with Python is pre-requisite.

Faculty mentor: Prof. Lars Gundlach
Chemistry & Biochemistry, Physics & Astronomy ● 🔗 Research Group Page
Graduate student mentor: TBD

Understanding the interaction between novel hybrid materials and THz radiation on time-scales as short as picoseconds is important for designing new and improving existing THz materials and devices. In this project the techniques and instrumentation necessary for measuring ultrafast THz response are applied, improved and developed. One focus of this project lies on implementing polarization-, temperature- and magnetic field-control in visible pump – THz probe spectroscopy. Students will work closely with the PhD student overseeing the project. They will be introduced to working with advanced ultrafast optical instrumentation and how to modify it for specific measurements. Students will learn how to conduct ultrafast time-resolved spectroscopic measurements, analyze the acquired data, and interpret the results.

Faculty mentor: Prof. Matthew Doty
Materials Science & Engineering ● 🔗 Research Group Page
Graduate student mentor: Maria Gamez

Quantum photonics are expected to enable major advances ranging from secure communication to improved quantum information processing. The participating REU student(s) will gain hands-on experience in designing and characterizing materials and devices for quantum photonic applications. For example, students might use Finite-Difference Time-Domain simulation methods to design new waveguides, cavities, or couplers. They might use scanning electron microscopy or atomic force microscopy methods to characterize materials or fabricated devices. They may help to develop and operate optical device characterization experiments. Through their engagement with these projects, students will deepen their knowledge of photonic devices and help to advance quantum technologies.

Faculty mentor: Prof. Yafei Ren
Physics & Astronomy ● 🔗 Faculty Page
Graduate student mentor: Randy Yeh

This project investigates how applying a magnetic field changes the way atoms vibrate in a solid and how geometric Berry-phase effects emerge in those vibrations. Students will learn to build and run simulations of lattice dynamics, visualize phonon motion, and interpret the role of quantum geometry in real materials. No prior experience is required—just curiosity and a willingness to learn computational tools used in modern condensed-matter physics.

Faculty mentor: Prof. Chitraleema Chakraborty
Material Science & Engineering, Physics & Astronomy ● 🔗 Faculty Page
Graduate student mentor: Abhijith Puthiya Veettil

The optical response of transition metal dichalcogenides (TMDCs) is dominated by excitons, where photoexcited electrons remain bound to the holes they leave behind through Coulomb interaction. A defining feature of these excitonic systems is their strong coupling to external conditions like magnetic field, electric field, and external dopants. This controllability positions TMDCs as promising platforms for quantum sensing and quantum information technologies. By stacking atomically thin TMDCs on magnetic substrates, we can create magnetic heterostructures where proximity effects from the underlying magnetic layer induce spin splitting and modify valley properties in the TMDC, offering an additional way for controlling excitonic behavior.

This project mainly focuses on optically studying these magnetic heterostructures, particularly the one based on Molybdenum Disulfide (MoS2). During the project, the student will assist in setting up and automating optical measurement tools for probing magnetic properties, such as magnetic circular dichroism (MCD). MCD measures how right-hand and left-hand circularly polarized lights are absorbed by the material in the presence of a magnetic field. Also, as the outcome of this project, students will get hands-on training on exfoliation and transfer techniques that are used to create these heterostructures and the characterization techniques which is used to characterize them. The aim of this project is to investigate how these proximity effects can affect the excitonic properties of the TMDCs and how we can tune it in a way that can be useful in future applications in quantum sensing.

Faculty mentor: Prof. Ryan Comes
Materials Science & Engineering Department ● 🔗 Research Group Page
Graduate student mentor: TBD

Molecular beam epitaxy (MBE) is commonly used to make ultra-high quality nanoscale materials for electronic, optical, and quantum systems. Reflection high energy electron diffraction (RHEED) is commonly used to study how nanoscale films are growing in MBE. We are working on development of machine learning codes to extract more information from RHEED data during synthesis to enable autonomous and AI-driven synthesis of these materials in the future. The REU student will work on developing machine learning codes to interpret RHEED videos and connect them to other data about the films that are grown in our lab. Students from materials science, physics, electrical engineering or computer science who have knowledge of Python coding and a bit of understanding of crystal structures are ideal for this project, where they will learn how to tie materials synthesis and characterization to new machine learning algorithms.