Professor Musgrave's research is focused on the use of computational quantum mechanics and machine learning to investigate important engineering processes at a fundamental level. His work comprises a range of technologies including: catalysis to split water to produce hydrogen, catalystic reduction of CO2 to hydrocarbons, polymerization and photopolymerization, advanced battery technology, pseudocapacitors, 3rd generation photovoltaics using singlet fission, organic catalysts and photocatalysts, photo initiators, solar thermal hydrogen production, and atomic layer deposition. Professor Musgrave is known for pioneering applications of quantum chemical simulations within chemical engineering and is often the first to provide detailed and fundamental descriptions of many important processes including atomic layer deposition, nanotechnology, singlet fission for carrier multiplication in organic photovoltaics, CO2 reduction and other catalytic systems.
computational materials science, computational chemistry, quantum chemistry, photovoltaics, energy storage, catalysis, photocatalysis, photochemistry, machine learning, photo initiators, photopolymerization, solar fuels, renewable, water splitting, CO2 reduction, fuels, electronic materials, thin film deposition, surface science, chemical kinetics, reaction mechanisms
CHEN 3220 - Chemical Engineering Separations and Mass Transfer
Studies separation methods including distillation, absorption, and extraction, and graphical and computer-based solutions to separation problems. Also studies mass transfer rate processes, including diffusion, microscopic material balances, and correlations for mass transfer coefficients. Applies mass transfer rate theory to packed and tray columns.