Research | Mayes Group

COMPUTATIONAL AND THEORETICAL CHEMISTRY RESEARCH

Development of Highly Accurate Quantum Chemistry Methods and Machine-Learning in Chemistry

The research goal is to develop predictive, highly-accurate, large-scale methods for excited states and open-shell systems which will pave a way to the rigorous modeling of excited states processes.

Another aspect of our work is application-driven which involves using computational methods to understand, simulate, and predict chemical and biological processes. Specific applications include:

Nonaqueous redox-flow batteries

Nonaqueous redox flow batteries (NRFB) have potential as a transformative technology for grid energy storage. We plan to address the fundamental challenges that constitute a critical knowledge gap in our current understanding of NRFB systems and require discovery and synthesis of new energy material. This is in collaboration with Cappillino research group. This work is funded through Marine and Undersea Technology program through ONR.

Self-assembly of peptide-based functional nanomaterials

The self-assembly of peptides has numerous potential applications in the fields of energy, nanobiotechnology, and nanomedicine. However, there is still a lack of fundamental understanding between structures and properties of these peptide-based materials. Such an understanding of the interactions, reactivity, and stability would help realize the potential of these materials. In collaboration with Vasudev research group.

Photochemistry and Dynamics

The photochemistry of several systems of interest, in gas-phase and on ice and mineral surfaces, will be studied through rigorous modeling using state-of-the-art excited state methods. The dynamics, branching ratios, energy distributions, lifetimes, and spectroscopic properties will be explored.

Catalytic Pathways and Dynamics of Desulfurization of Petroleum Feedstocks

There has been much interest in clean transportation fuels with emphasis on sulfur content reduction. The existing desulfurization technologies such as hydrodesulfurization are no longer sufficient for the “deep refining” needed to meet more severe restriction on the amount of sulfur. This work aims to understand the reactions involved in the desulfurization of fossil feedstocks which will guide improvements in the selection of catalysts and improved efficiencies of fuel production.