Chemistry & Biochemistry
For additional information on research in Chemistry & Biochemistry, see:
Raman Spectroscopic Imaging and Trace Detection
The Schultz lab is interested in developing Raman spectroscopy for the identification of chemical species. Applications range from identifying chemicals in living plants to identifying chemical changes in cells and tissue resulting from exposure to radiation. We are also interested in understanding spatially resolved chemical profiles related to biological activity and are actively developing new methods to image molecular properties.
Molecular Biology & Enzymes
The Jackman lab investigates the biochemical mechanisms of enzymes that catalyze key reactions during the maturation of the critical non-coding RNA molecule, tRNA. We study enzyme that utilize unusual chemistry for biological reactions, and use the tools of mechanistic enzymology (kinetics, protein engineering, biophysical structural approaches) combined with the power of model organism genetics to make new discoveries about the molecular mechanisms and biological functions of these unusual enzymes in living cells.
The Magliery lab studies the sequence basis of protein stability and other physical properties using high-throughput, statistical, and rational approaches. Summer students could participate in fundamental studies in protein stability or in applied protein engineering for diagnostic or therapeutic purposes.
Molecular Biology & Enzymes
Projects in the Musier-Forsyth lab are focused on characterizing protein-RNA interactions involved in HIV-1 replication and fidelity mechanisms in protein synthesis. Undergraduate students will learn techniques such as protein and RNA purification, enzyme kinetic assays, RNA structure-probing, and characterizing RNA-protein binding interactions.
Peptide Chemical Biology
The student will be involved in the synthesis, purification, and biochemical/cellular characterization of macrocyclic peptides as potential therapeutic agents against intracellular protein-protein interactions.
Research in the Thomas laboratory focuses on the design of functional catalysts using Earth-abundant transition metals for the development of more sustainable and environmentally friendly technology. The summer project will involve the synthesis and characterization of new transition metal complexes and their use as catalysts for both the activation of naturally abundant small molecules (e.g. carbon dioxide, water, oxygen) and/or organic transformations. Over the course of the summer project, students will learn how to synthesize and manipulate air and moisture-sensitive inorganic and organometallic complexes using glovebox and Schlenk techniques, as well as a variety of spectroscopic and analytical methods such as NMR, IR, and UV-Vis spectroscopies and cyclic voltammetry.
Solar Energy and Batteries
The research in Yiying Wu’s group focuses on functional materials for energy conversion and storage. The projects include developing solid and liquid electrolytes for Li and K batteries, photoelectrochemistry of semiconductors for solar fuels, and organic-inorganic hybrid materials for quantum materials and spintronics. The students will participate in the design and synthesis of these materials, their structural characterization, and measurements of their properties.
Inorganic Synthesis and Energy
We are a group of chemists utilizing synthetic inorganic chemistry to tackle unmet challenges at the frontiers of energy storage and energy conversion. Group members can expect to gain experience in the synthesis of organic, inorganic, and organometallic compounds, characterization of air-sensitive/temperature-sensitive complexes, spectroscopy, electrochemistry, and battery fabrication techniques.
Computational Chemistry, Synthesis and Enzymology
The Hadad research team uses computational modeling, organic synthesis and biochemical evaluations to design, synthesize and evaluate the efficacy of novel drug-like compounds for the treatment of organophosphorus poisoning. An undergraduate student could be involved in one of these approaches as part of our research team, perhaps doing computational modeling for the design of novel therapeutics or the synthesis, characterization and biochemical evaluation of individual compounds for in vitro studies.
The student will work on our battery program. The student will synthesize organic compounds that can store electrons and will benchmark their physical properties/stabilities. The student will gain experience in organic synthesis and electrochemistry while also learning about the battery sciences.
Material Science and NMR
Undergraduate students working with Professor Grandinetti will apply multi-dimensional NMR spectroscopy and machine learning to extract structural distributions in glasses. These distributions reveal details on modifier cation clustering, ionic transport, the mixed alkali effect, chemical strengthening, and phase separation in glasses. Such insights help glass scientists and engineers working on the next generation of specialty glasses, impacting diverse applications such as handheld electronic devices, displays, optical fibers, glass substrates for lighting, bio-glass implants, and nuclear waste storage.
Research in the Herbert group focuses on the development of electronic structure theory. Projects include computational spectroscopy of both molecules and materials, often in complex environments, and development of theoretical tools to understand the nature of chemical bonding and of noncovalent interactions.
One of our current major projects deals with providing a molecular and structural basis of the amyloid strain and transmissibility barrier phenomena for a family of mammalian Y145Stop prion protein variants. To this end we are undertaking the structural studies of supramolecular amyloid fibril aggregates composed from these proteins by using advanced multidimensional solid-state NMR spectroscopy techniques supplemented by additional biochemical and biophysical experiments. Other major research directions in the group involve studies of chromatin structure and dynamics by solid-state NMR, and the development of new solid-state NMR methods for protein structure determination based on paramagnetic tagging.
Femtosecond Laser Spectroscopy and Nanoscience
We use time-resolved laser spectroscopy to understand the dynamics of excited electronic states in carbon-based nanomaterials, which are of interest for sustainable energy conversion and storage. Summer students can gain skills in optics and optical instrumentation, learn some molecular and supramolecular photophysics, synthesize synthetic melanin, and use lasers to measure events that are over in just trillionths of a second.
Knowledge of protein structure is paramount to the understanding of biological function and for developing new therapeutics. Mass spectrometry experiments which provide some structural information, but not enough to unambiguously assign atomic positions have been developed recently. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. We are developing integrative modeling techniques, computational modeling with mass spec data, that enable prediction of protein complex structure from the experimental data.
Computational Chemistry and Theory
Summer projects in the Sokolov group will focus on computer simulations of excited states and spectra of molecules and materials with complicated electronic structure. Students will use state-of-the-art quantum chemical methods to understand properties of molecules and materials important in photochemistry and catalysis. Students will also use computer programming to analyze the results of calculations and will have an opportunity to participate in the development of new theoretical methods.
For additional information on research in Mathematics, see:
Computational Number Theory
We will use computational methods to study “arithmetic biases” in the prime numbers. The prime numbers are the building blocks of all the natural numbers using multiplication. A highly successful approach to understanding the primes is to model them using random variables that are fair. “Bias” occurs when the actual behavior of the primes does not conform to our fair random model. Examples of this include the so-called Chebychev bias and, more generally, prime number races. And there are other surprising examples discovered in the last few years. The discovery of such biases is interesting because the well-known Riemann hypothesis tells us that the primes should in a sense be randomly behaved. Prior familiarity with elementary number theory and some mathematical software would be useful, but not essential.
For additional information on research in Microbiology, see:
Protein Synthesis in Bacteria
The Fredrick lab studies mechanistic aspects of ribosome assembly and function. Summer students would learn molecular and biochemical techniques such as gene cloning, mutagenesis, protein purification and enzyme assays.
Natural Products Drug Discovery
The Ju lab integrates genomic, metabolomic, biochemical, and genetic methods to accelerate discovery of new microbial natural products and the mechanisms of their biosynthesis. Summer students will employ a combination of these techniques to reveal new chemical diversity encoded within microbial genomes important for drug discovery.
Viral Discovery, Virocells, and Phage Therapy
The Sullivan lab studies viruses of microbes and has a long and strong history of training undergraduate researchers. We have established quantitative viral metagenomic sample-to-sequence pipeline and community-available informatics platforms to analyze such data, expanded our understanding of the global virosphere, and developed approaches to link and explore virus-host interactions. While our research initially focused on ocean viral ecology and evolution, we now apply these approaches to soils, humans, and extreme environments to understand their diversity and impacts, as well as establish them as practical tools for treating disease (e.g., phage therapy).
For additional information on research in Physics, see:
Bioinformatics and Statistical Physics
The Bundschuh lab studies the interactions between nucleic acid molecules (DNA and RNA) and proteins using computational methods from Statistical Physics and biological sequence analysis. High throughput sequencing has made it possible to obtain exquisitely detailed information on nucleic acids protein interactions but it requires the analysis of large data sets in order to extract biological knowledge from the sequencing data. Students will learn how to perform such data analysis on one (or more) of several experimental collaborators’ data sets and hopefully discover new insights into the Biology involving nucleic acid protein interactions.
Ultrafast Laser Spectroscopy
We are constructing a novel instrument to study the laser/matter interaction on ultrafast time scales (10-15s) and with atomic spatial resolution (10-10m). Initial targets will be to study how surfaces are modified under intense laser irradiation, with a goal to image individual atomic vacancies and other defects as a function of laser fluence, time etc. We have recently been awarded funding from the Air Force Office of Research to purchase components and develop this instrument. During the summer, we anticipate completing the system integration. Anticipated work items will be to characterize the performance of the ultrahigh vacuum chamber that houses the instrument, atomic resolution imaging of test surfaces to characterize microscope noise performance, testing of optical components, general lab setup, other component purchasing and CAD hardware drawings to confirm system integration. We anticipate that the summer REU student would work closely with a team of 2-3 other students, both graduate and undergraduate. We would also encourage the REU student to take advantage of professional development opportunities provided through the universities’ SROP program, and the Physics Departments’ CEM REU program. These include report writing, presentation, preparation for graduate school etc. These ongoing programs also provide a network and community for summer students outside of the lab.
Physics Education Research
There is a growing consensus that computer science should be integrated into high school and early college courses like physics and math, but there has been relatively little research performed to determine the best way to do this. The STEMcoding project, led by OSU Physics faculty Prof. Chris Orban and University of Mt. Union faculty Prof. Richelle Teeling-Smith, exists to fill this void by building science and math-focused coding activities and creating and validating assessments of student learning. In order to encourage science and math teachers to experiment with coding activities in their courses, the STEMcoding project also has a YouTube channel (https://youtube.com/c/STEMcoding) where they post coding tutorials and other helpful content. The focus of the internship will be education research, but students will have the option of contributing to the YouTube channel, as well. Dr. Orban is especially interested in working with students who intend to be high school math or statistics teachers.
Chromatin Biophysics and Single-Molecule Spectroscopy
The Poirier lab investigates the physical properties of the human genome and how these properties regulates gene expression. Undergraduate Students will participate in studies that could include the preparation of DNA-protein complexes that mimic how genomic DNA is organized in chromatin, preparation and application of DNA origami nano devices for studying chromatin structural dynamics, and application of single molecule fluorescence and force measurements to characterize chromatin structure dynamics and function.
For additional information on research in Public Health, see:
Dose-Response Modeling of High-Throughput Transcriptomic Data in Chemical Toxicity Studies
Transcriptomics, the study of RNA molecules produced by a genome, is a useful tool in toxicity studies since it can provide insight on the effects of a chemical on gene pathways leading to disease. The National Toxicology Program (NTP) has developed a novel transcriptomic gene set which can be used within a Next Generation sequencing platform to rapidly examine the effects of a chemical on approximately 2700 unique RNA copies (transcripts). The goal is to determine, for each pathway, the smallest dose that causes a biologically significant increase in pathway activity above a zero-dose control (the benchmark dose [BMD]). The analysis approach taken by the NTP involves fitting different dose-response curves to each transcript and reporting a summary BMD for each pathway. Although conceptually reasonable, there has not, to my knowledge, been a formal statistical evaluation of the method. In particular, it is unclear if the NTP’s method for selecting which transcripts to model produces unbiased estimates or if their approach to calculating a 95% lower confidence limit (benchmark dose lower bound [BMDL]) produces an interval with 95% coverage. The goal of this summer project will be to design and implement a simulation study evaluating the NTP’s approach to BMD estimation in transcriptomic studies. The student will learn the basic principles of dose-response assessment and be introduced to the EPAs Benchmark Dose Software. They will also have hands-on experience working with data from a real toxicogenomics study. The project will involve a fair amount of coding using a package such as R or Matlab; some related coding experience is desired but not required.
Greg Rempala and Eben Kenah
Monitoring, Vaccination, and Social Distancing to Control COVID Infections on College Campuses
Over past 2 years, many US universities have struggled with assessing risk of COVID-19 infections due to in-person instruction and other activities on college campuses. This research will look at some synthetic data inspired by the OSU experience that will help assess the risk of classroom infections as a function of the epidemic intensity and the levels of compliance with vaccination and mask wearing policies. Although not necessary, some experience with programing in R will be useful.
Cancer Health Equity
Dr. Ewing’s research is designed to reduce cancer health inequities by promoting cancer education and increasing access to cancer screenings for underserved and minority communities by leveraging Community-Based Participatory Research. For a summer project, students may learn from meetings with community stakeholders, engage in literature reviews for manuscript development and publication, research study design, instrument development, and/or data collection and analyses.
Racial Disparities in Gynecologic Cancer
As a cancer epidemiologist, my work focuses on racial disparities in the incidence and survival of women with gynecologic cancers. In my research I conduct both primary and secondary data analyses. Examples of primary data collection projects include a study of inflammation changes in endometrial tissue among white and black women at high risk of developing endometrial cancer; a study of patient-reported outcomes among endometrial cancer survivors; and an investigation of vaginal tampon and blood samples from patients diagnosed with endometrial cancer to identify molecular biomarkers for disease recurrence. In secondary data analyses, I typically use data from the National Cancer Database to explore disparities in treatment receipt and survival according to the social determinants of health (income, education, health insurance coverage, etc.).
Substance Use in Low-Income Populations
My research focuses on tobacco control, including smoking cessation, tobacco use surveillance, tobacco policy and tobacco regulatory science. A project that I co-lead is a smoking cessation intervention for women who receive medical care at any of the 10 healthcare systems participating in our project. These systems are located in the Appalachian regions of Ohio, Virginia, Kentucky and West Virginia. I am also co-leading a project related to hookah smoking among young adults. Both of these projects are funded by the National Cancer Institute. I am also actively involved with several projects funded by the Ohio Department of Medicaid, including the Ohio Medicaid Released Enrollees Study, the Ohio Medicaid Assessment Survey, the Ohio Medicaid Community Engagement Evaluation, and the Interviews of Mothers on Medicaid. These projects serve to inform the programmatic goals of the Ohio Department of Medicaid. I have examined many outcomes in these studies, but the main focus has been on tobacco and other substance use.
Racial and Socio-Economic Disparities in Psychiatric Care and Outcomes
I study how ambient or macro-social phenomena (such as economic recessions) and policy or programmatic changes (e.g. new health or social policy, cash transfers) impact mental health outcomes in a population. I am particularly interested in how these exposures influence racial and socio-economic disparities in psychiatric services utilization, deaths of despair (suicides, overdose, alcohol use-related mortality). Some of my key research findings thus far include the following: (1) populations, on average, increase risk-averse behaviors during ‘difficult’ times (e.g. during economic recessions), but these aggregate trends mask increased adverse psychiatric outcomes among vulnerable groups (such as low-income children and racial minorities), (2) improved socio-economic status in vulnerable groups (e.g. American Indian/Alaska Native) corresponds with increased optimism about the future, and (3) populations under stress exhibit scapegoating behavior where they target racial minorities for socially sanctioned micro-aggressions (e.g. involuntary psychiatric commitments).
For additional information on research in Statistics, see:
Among the most convenient models of physical processes are cellular automata (CA), which are deterministic models, and interacting particle systems (IPS), which are stochastic models. Broadly understood, CA and IPS describe evolving configurations on a fixed network, which update using local rules that are the same across time and space. CA and IPS are used to model natural phenomena and gather insights into fundamental organizational principles in many scientific fields. Motivated by studying self-organization, potential projects involve evolution of a given CA or IPS rule from a random initial state. The tools used will encompass probability theory, combinatorics, and computer simulation.