Multi-Physics Modeling: Catalysis and Materials for Clean Energy
The Senftle Group develops and applies computational modeling tools for assessing complex, multi-component catalysts at both the electronic and atomistic level. Particular focus is placed on developing fundamental structure-activity relationships informing the rational design of catalytic systems for efficient energy conversion, storage, and utilization.
Unraveling the Nature of Complex Metal-Support Interactions in Catalysis
Heterogeneous catalysts featuring transition metal nanoparticles supported on oxide surfaces play an essential role in energy, environment, and chemical technologies. Synergistic interactions between the supported metal and the oxide surface can alter catalytic behavior and therefore must be understood at a fundamental level to tune overall catalytic activity, selectivity, and stability. Such interactions are complex, often resulting from the simultaneous action of multiple independent phenomena. We employ density functional theory (DFT) in concert with screening approaches derived from machine learning (ML) to identify generalized descriptors that control metal-support interactions. This approach provides predictive models that can identify useful modifications of the support or cluster morphology via the introduction of defects and dopants. Beyond catalysis, we develop methodologies for uncovering the fundamental properties responsible for governing charge transfer interactions in other multi-component systems, such as electrodes employed in photovoltaics, batteries, and fuel cells.
Simulation of Complex Semiconductor/Electrolyte Interfaces
Effective, affordable solar energy conversion devices will require the discovery of novel materials that are both efficient and inexpensive. There is an emerging interest in photoelectrochemical devices that employ electrodes capable of harvesting photons while at the same time providing active surface sites for heterogeneous catalysis. To design such electrodes, one must have a fundamental understanding of interactions occurring between the electrode and the reactive electrolyte environment it is exposed to during operation. The ability to model multi-component surface structures with atomic resolution is therefore crucial to the rational design of advanced photochemical electrodes. DFT calculations, employing the formalism of ab initio thermodynamics, are used to predict stable surface structures on electrode materials that show promise for use as either anode or cathode components in photoelectrochemical cells. The ReaxFF potential is used to model dynamic surface/electrolyte interactions occurring at scales beyond the computational reach of DFT. Together, ReaxFF and DFT reveal how the dynamic interplay between the surface and the electrolyte affects charge transfer.