Click on each project title to find a description of the lab and any preferred background. Many of these labs are interdisciplinary, so please look through projects that are housed in other departments.
We will be adding more labs during the weeks, so please come back to check out any additional labs that have been posted.
Project Description: We are exploring a novel class of semiconductors with large density of states (high absorption coefficient and carrier density) with tunable structure and composition. We have already demonstrated materials with a world record high birefringence (different refractive index along the optic axis and other principal axis) and properties suitable photovoltaic applications. We use crystal growth to produce high quality materials for these investigations. We are expanding our efforts to thin film growth of these materials now.
Related Background: Candidates will have a background in materials science, physics, chemistry, or related engineering disciplines. Coursework in thermodynamics and solid state physics is typically helpful.
Prerequisites: Basic Materials science related classes (Physics/Chemistry/Engineering)
Faculty: Shaama Sharada
Project Description: Supported single atom catalysts are touted as being highly efficient and economical compared to supported precious metal nanoparticle catalysts. However, the activity and stability are dependent on operating conditions and reactants/products involved. We use quantum chemical and dynamics approaches to probe these dependencies and design catalysts for various applications including preferential oxidation for fuel cell feed.
Related Background: Some prior experience with quantum chemistry/molecular dynamics simulations desirable
Prerequisites: Kinetics
Faculty: Shaama Sharada
Project Description: While manmade processes for conversion of natural gas resources to useful products require extreme temperatures and pressures and lots of energy, enzymes found in bacteria can carry out highly selective transformations under ambient, mild conditions. Our goal is to demystify these processes and uncover new catalysts using clever quantum chemical strategies for probing mechanisms and predicting catalyst compositions.
Related Background: Some experience with quantum chemical/molecular dynamics simulations desirable
Prerequisites: Kinetics
Faculty: Shaama Sharada
Project Description: While machine learning methods are rapidly and successfully being adopted for predicting material and chemical properties, the inverse problem of predicting novel materials with desired properties is still in its infancy. We are implementing deep learning frameworks to address this problem and to explore the chemical space based on electronic and steric properties of ligands in transition metal complex catalysts.
Related Background: Introductory machine learning course desirable
Prerequisites: Python/programming
