Pretzie’s research focuses on the use of Density Functional Theory (DFT) tools and thermodynamic formalisms to study the stability and activity of carbon atoms embedded in amorphous carbon structures. The goal is to determine their suitability for methane activation to form ethylene, a critical industrial chemical used in the production of plastics, pharmaceuticals, and more.

While at Argonne, Pretzie will help develop machine learning models to accelerate the theoretical exploration of catalysts, particularly for the Non-Oxidative Coupling of Methane (NOCM) reaction. This work aims to enable the conversion of methane-abundant in natural gas reserves-into ethylene without releasing carbon dioxide, addressing a major challenge in current industrial processes.

“My CISTAR research involves using DFT to better understand how carbon-based catalysts may participate in the NOCM reaction,” Pretzie explained. “This program will allow me to work on developing machine learning models to expedite the process of determining the thermodynamics and kinetics of NOCM on various carbon catalyst models. These models could also help future researchers analyze a wide range of catalysts more efficiently.”

Pretzie expressed gratitude to his advisor, Prof. Jeffrey Greeley, his DOE SCGSR mentor, Dr. Cong Liu, as well as Dr. Maria K.Y. Chan, Prof. Robert Warburton, Dr. David Kaphan, and the faculty and staff of CISTAR for their support throughout his PhD journey. 

The DOE SCGSR Program provides outstanding U.S. graduate students with opportunities to conduct part of their thesis research at a DOE laboratory in collaboration with a DOE laboratory scientist. The program is designed to prepare graduate students for scientific and technical careers critically important to the DOE Office of Science mission.