Research Areas
Atomistic Simulation using Quantum Chemical Simulations for Energy Applications
Our research program focuses on modeling molecular processes in important engineering problems. We aim to develop an accurate atomic-level understanding of physicochemical phenomena related to molecules, solids and interfaces using state-of-the-art quantum chemical software packages. These software packages, along with advanced supercomputing resources, allow us to determine the ground state geometry of systems relevant to energy conversion applications, which in turn illuminate thermodynamic, kinetic and physcial properties. Members of our group combine expertise in chemistry, physics, materials science and chemical engineering, along with extensive experimental collaboration, to solve some of the most challenging engineering problems known.
Catalysis and Electrocatalysis
The chemical and fuels industries are built upon chemical transformations that are otherwise too costly or too slow. Many of the largest social advances of the 20th century were afforded to us by advances in catalytic technology, such as the famous Haber-Bosch process which solved the fertilizer shortage, or the development of the catalytic converter to clean up automobile exhaust. The need for advances in catalysis has not diminished, but the nature of those needs, and in particular the nature of available solutions, has changed. Recently, the price of renewable electricity has fallen to a level that makes electrocatalytic (reactions driven by electrical energy rather than thermal) conversions a promising avenue. In the Musgrave group, we are interested in modeling structure-activity relationships at the electrochemical interface, which has a high degree of complexity. Specifically, we use that includes an applied potential in the solution, to examine how electrocatalytic reaction mechanisms and materials change as a function of potential. We have recently shown that this approach captures behavior that is either , or . We are now using these tools, in collaboration with multiple groups (Sundararaman - RPI; Sutton - UofSC; Vigil-Fowler - NREL; Del Ben - LBNL), to create , which we hope will help all electrocatalysis researchers in their quest for designing and understanding the next-generation of catalyst materials. Additionally, we work with experimental groups (Dismukes - Rutgers; Velázquez - UC Davis; Hatzell - Georgia Tech) to validate our computational results with experiments.
Novel Perovskite Material Discovery
Perovskites are an exciting class of materials that follow the general chemical formula ABX3, where A and B are some cation (alkali metal, alkaline earth, transition metal or organic molecule) and X is some anion (halide and oxide are the most common). Perovskites have been identified as interesting materials for many energy applications such as catalysis, electrochemical devices and photovoltaics. One of the limiting factors for developing pervoskites is the massive compositional space that exists (there are easily hundreds of thousands of different compositions possible). Not only is it not efficient to experimentally screen all of these compositions, it is not particularly efficient to use quantum chemical methods like DFT to screen them either, owing to the often large structures required for accuracy. In the Musgrave group, we have developed a framework to, with relatively high accuracy, conduct pre-DFT screening on candidate compositions and structures to evaluate which structures are viable for more detailed study. Our new, predicts perovskite forming compositions with greater than 90% accuracy, and recently we reported a to determine stability of predicted perovskite compositions. Along with our collaborators at Sandia National Laboratory, the National Renewable Energy Laboratory, the Renewable and Sustainable Energy Institute at ¶¶Òõ¶ÌÊÓƵ and the Materials Project, we are able to rapidly discover, test and re-optimize our models for perovksite materials, as we recently demonstrated for .
Organic and Organometallic Molecule Design
Homogenous catalysis, while not as prevalent as heterogenous catalysis, is a powerful tool for especially tricky chemical transformations that require high levels of regio- and chemical selectivity. Unlike bulk solids, molecular catalysts have discrete electron orbital energy levels that can be tuned with ligand chemistry. As such, there is a modularity to homogenous catalysts that can be exploited to achieve extrememly efficient, enzyme-like, catalysts. In the Musgrave group, we explore the ligand/functional group interactions that drive reactivity trends in molecular catalysis. These catalysts include organometallic complexes as well as metal-free organocatalysts. By adopting a molecular orbital-driven approach and using high-fidelity DFT methods, in conjuction with our experimental collaborators from the Luca group (¶¶Òõ¶ÌÊÓƵ - Chemistry) and Glusac group (UIC - Chemistry), we have developed , metal-free CO2 and molecules. In addition to our ongoing work in molecular catalysis, we use the lessons taught to us to inspire which catalyst materials may be useful in heterogenous catalysis, as we strive to achieve the same level of activity and selectivity in those systems.
