(7dd) Computational Design of Surfaces and Nanostructures for Energy Applications

-Efficient materials screening and design, particularly for catalysts:

Adsorption energies are good predictors of catalytic performance, but calculating adsorption energies on a large number of potential catalytic surfaces remains a challenge. I have developed methods for efficiently and accurately predicting adsorption energies of important intermediates on transition metal surfaces. These methods are quite general, applying to any transition metal alloy surface, and linking any adsorbate to electronic structure or to any other adsorbate. They are also efficient and physically transparent, allowing high-throughput screening or rational design. Future work will involve applying these methods to design novel catalysts (particularly those that break traditional scaling relations), and further improving their accuracy, efficiency and applicability.

More generally, machine-learning methods will be applied to develop improved molecular dynamics methods, based on an ensemble of simple force-fields. This will allow would allow accurate, efficient studies of long-time scales and rare events, based on relatively small datasets.

-Excitations in metals and metal interfaces, for catalysis and solar cells:

Since metals have no bandgap, reactions on metal surface may induce electronic excitations, which could affect surface chemistry. However, most studies of processes on metal surfaces assume that the system remains in the ground state. Using an efficient nonadiabatic dynamics code employing density functional theory and Ehrenfest dynamics, I have tested this assumption for nitrogen dissociation on Ru. These calculations show that even in thermal catalysis, surface processes can excite electrons in metal surfaces, and these excitations can affect surface chemistry. Future work will focus on light-induced excitations (e.g., plasmons) in metal nanoparticles and hybrid systems involving metals and supports or molecules. This will bring improved understanding and design principles for plasmonic solar cells and plasmonic catalysis.

Teaching Interests:

-Mathematical methods

-Materials chemistry and structure

-Thermodynamics

-Fluid dynamics and transport

-Quantum and computational chemistry and materials science