Our program unites various modern and classical tools for the design of catalysts for new reactions with broad applications from enantioselective synthesis to energy related topics (fuel cells and batteries) to biological inspired reaction types (C–H functionalization, directed evolution). Our goals are not only to enable the development of processes with the wide-ranging applications described above but ultimately to understand the guiding principles by which the performance of a particular catalyst or functional molecule is achieved. To accomplish this, we have been integrating classical techniques of physical organic chemistry with a new set of methods to interrogate the complex relationship of structure to function. To explore these broad topics, we are currently engaged in the following projects:
Pd-Catalyzed Alkene Functionalizations (Funded by the NIH)
The selective functionalization of Pd-alkyl intermediates requires a careful understanding of the dynamics of β-hydride elimination, migratory insertion, and transmetallation. Our lab has been interested in exploring palladium’s tendency towards facile β-hydride elimination as a means by which to transpose palladium to a desired position on a substrate for subsequent functionalization, empowering a number of useful C–H, C–O, and C–C bond-forming reactions.
- New Catalysts and Synthetic Applications for Alkene Functionalization Reactions
- Pd-Catalyzed Alkene Difunctionalization Reactions
- Pd-Catalyzed Alkene Hydrofunctionalization Reactions
- Enantioselective Redox-Relay Heck Reactions
Enantioselective Catalysis and Ligand Design: Physical Organic Chemistry in Catalyst Design using Multidimensional Optimization (Funded by the NSF)
Our group has also been associated with multivariate linear regression techniques to facilitate the design and implementation of new bond-forming reactions. Using these modeling techniques, one can identify statistically significant correlations to validate, and more importantly, predict a reaction’s outcome. This type of approach can be critical to probe a reaction mechanism and inform the design of superior-performing catalysts. To this end, we have initiated a program that unites optimization with mechanistic interrogation by correlating reaction outputs (e.g., enantio, site, or chemoselectivity) with structural descriptors of the reagents, substrates and catalysts involved.
- Physical Organic Chemistry in Catalyst Design using Multidimensional Optimization
- Utilizing Classic and Modern Physical Organic Tools in Design of Experiments
- Parameterization of Ligands for Asymmetric Catalysis (pyrox, box, chiral phosphoric acids, etc.)
- Mechanistic Investigations to Elucidate Non-Covalent Interactions
- Prediction of Reaction Outcome Through Ligand Library Virtual Screening
Member of the NSF Center for Stereoselective C-H Functionalization (website)
As a member of the CCHF, we are currently involved in collaborative projects focused on the design of new catalysts for C–H functionalization. We are also working on methods to elucidate the subtle effects that determine site selection in the context of reacting a single C–H bond in a molecule.
- New catalyst and ligand design
- Developing new optimization tools with the potential to interrogate reaction mechanism
- Exploring the origins of reagent, substrate, and catalyst control in site selective reactions
Electrocatalysis/Redox Flow Batteries
Our lab is interested in utilizing electrochemical techniques to develop new reaction methodology. This type of strategy can replace chemical oxidants with an electrode to tune the potential for a desired transformation. Developing a fundamental understanding of homogenous electrochemical processes can allow for the design of highly active catalytic materials.
Working in the Joint Center for Energy Storage Research (JCESR), we are combining electrochemical techniques with multidimensional modeling strategies to design highly stable redox active species that can be used as anolyte/catholyte materials in redox flow batteries.
TEMPO-mediated electrochemical oxidations
New materials for redox flow batteries
Applying multivariate modeling techniques to predict electrochemical outcomes