Stochastic Processes in Electrochemistry
Rich and new information about a chemical system can be learned by directly probing the individual entities (e.g., single cell, single nanoparticle, and single molecule). Such single entity studies demonstrate many advantages over traditional ensemble measurements, including simplicity (free from interactions between the entities) and ultra-high resolution.
We'll combine the tools of electrochemistry, statistics (e.g., machine learning), and computer simulation to tackle questions in energy conversion and storage on heterogeneous surfaces. Our goal is to elucidate the nature of active sites for important catalytic reactions including hydrogen evolution reaction (HER), oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and CO2 reduction (CO2R). The results will guide better design of electrochemical energy conversion systems, including fuel cells and electrolyzers.