Computational Design of Carbone Catalysts
The Ogba Lab is looking for students eager to work at the interface of organic chemistry, high-performance computing, and data science. This is a funded, full-time, 10-week program scheduled for Summer 2026. On-campus housing support is included.
In my lab, we seek to accelerate chemical reaction design by using computational tools to generate robust, data-driven mechanistic hypotheses. This eliminates the costly and time-consuming trial-and-error bottleneck common in traditional chemical discovery.
Our current focus is on carbones, unique zerovalent carbon compounds with untapped potential as metal-free catalysts.
This summer, you will be simulating chemical reactions using quantum mechanical modeling and/or machine learning models to design catalysts that can turn industrial waste (like CO2) into valuable chemical feedstocks.
You will join one of two externally funded research tracks:
- NSF: Deep-dive into the underpinnings of carbone catalysis. Map out reaction coordinates to understand exactly how structure dictates function in carbone-mediated hydroborations.
- ACS PRF: Model reaction pathways to discover thermally stable and high-efficiency carbone catalysts capable of fixing CO2 into N-methyl amines.
Outcomes
This is an opportunity to build a high-demand skill set that bridges chemistry and computer science:
- Master industry-standard software (Gaussian, Schrödinger) and High-Performance Computing (HPC) workflows (SLURM/Linux).
- Move beyond explaining chemistry to predicting it. Generate and analyze large datasets to build ML models that identify high-performing catalysts faster than human intuition allows.
- Present your findings and potentially contribute to peer-reviewed manuscripts.
Expectations
- To ensure you hit the ground running in summer, you are expected to attend weekly research group meetings through the Spring 2026 semester: Thursdays, 5:30 pm – 6:30 pm.
- The full-time commitment in Summer 2026 includes daily research activities, weekly individual mentorship meetings, and group meetings and discussions focusing on research projects.
To apply, please submit an essay response that addresses the prompts below. Please visit our research website, review the Lab Syllabus, and read our short forum piece (attached to this posting) before writing.
Essay Prompt:
- Which aspect of the projects in my lab appeals to you most? Are you drawn to the fundamental physical organic chemistry (e.g., unraveling complex CO2 reduction mechanisms) or the data science application (e.g., building predictive models for thermal stability)? Why?
- Read Schernikau and Ogba (2025) - "Effect of strain and π-acidity on the catalytic efficiency of carbones in carbodiimide hydroboration." Pose 1-2 insightful scientific questions about the methodology, results, or implications of this work.
- What is your background in organic chemistry, computational methods, or data science? (Note: I value curiosity and aptitude over a perfect resume. If you have coding experience, Python/MATLAB, or a background in physical chemistry/physics, tell me about it.)
- What do you hope to gain from this specific research experience, and how does it connect to your post-graduation career goals (e.g., PhD, Industry, etc.)?