Computational Materials

Computational materials research is firing on all cylinders, driving the discovery of new materials well beyond the computational realm! In our lab, our research spans three main branches: modeling and simulation, software and hardware development, and wet-lab synthesis and characterization. 

• Modeling & Simulation. Students build a foundation in math, physics, and chemistry to understand how reaction mechanisms can be described and designed, while also developing basic programming skills to create and use tools for identifying reactions and modeling materials. Our simulation research projects are often in collaboration with experimental groups, such as the Humphrey Group (inorganic chemistry), the Hull Group (organic chemistry), the Ren Group (electrochemistry), and the Zheng Group in Chemical Engineering. The research topics revolve around catalysis and battery material designs, such as studying catalysts for methane activation, hydrogen evolution reactions, proton/zinc/lithium batteries. These projects explore topics such as catalysis and battery materials, including catalysts for methane activation and hydrogen evolution reactions, as well as proton, zinc, and lithium batteries.
• Software & Hardware Development. This branch focuses on creating new tools that use machine learning potentials to accelerate materials research. One of our starting projects is the “Feel the Force” haptic device, which translates the forces acting on an atom into physical feedback, allowing researchers to actually feel where atoms are being tugged and pulled. Researchers can then use their chemical intuition to guide atoms and explore reaction landscapes that may be difficult for algorithms to navigate efficiently. Our research aims to make molecular systems more tangible by developing a haptic device designed specifically for materials scientists. Our team is building the device from the ground up to create a new, more intuitive way to interact with and explore molecular systems.

Our strategy is to build a strong interdisciplinary foundation and then give students the flexibility to develop in the direction that best fits their interests. Students begin with the fundamentals of math, chemistry, physics, and computer science while building practical skills in Python and Linux bash scripting, with opportunities to learn specialized languages such as FORTRAN.

 

As students gain experience, they can shape their own research path, whether developing computational solutions for experimental researchers, building new tools for materials scientists, or combining computation and experiment to approach materials research from both sides.

 

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We are bridging computation and wet-lab experimentation to accelerate materials discovery! By combining molecular modeling, machine learning, innovative research tools, and wet-lab synthesis and characterization, our research moves ideas from computational prediction to experimental testing. This integrated approach allows us to tackle challenging problems in catalysis, energy storage, lithium extraction, and rare-earth element separation while developing new ways for scientists to design, explore, and understand materials.