New Methods for Ammonia Electrosynthesis Modeling
ChE Assistant Professor Qing Zhao was awarded a $537,226 NSF award for “Automated Embedded Correlated Wavefunction Theory for Kinetic Modeling in Heterogeneous Catalysis.” The research will investigate ammonia production with a goal of developing advanced computational modeling tools to understand fundamental chemistry in ammonia synthesis powered by renewable electrical energy/stored electrons.
Abstract Source: NSF
With the support of the Chemical Catalysis program in the Division of Chemistry, Qing Zhao of Northeastern University is developing advanced computational modeling tools to understand fundamental chemistry in ammonia synthesis powered by renewable electrical energy/stored electrons. Ammonia is a critical component in fertilizers and an ideal zero-carbon energy carrier. If one could achieve the electrochemical production of ammonia using nitrogen gas and water at ambient temperature and limited pressure with a favorable kinetic profile, one would have a more sustainable technology to replace the traditional industrial Haber-Bosch process for ammonia production, which consumes tremendous amounts of fossil fuel and emits massive amounts of carbon dioxide. A reliable understanding of reaction mechanisms is foundational in designing more efficient electrocatalysts. This research aims to develop high-level quantum mechanical simulations beyond the conventional modeling tools to elucidate this important catalytic transformation. This project will integrate multiple educational activities and outreach in a workshop to help K-12 teachers develop curriculum materials on the topics of computation, catalysis, and sustainability, aiming at advancing excitement about science in a more diverse scientific community.
Under this award, Qing Zhao and her research team at Northeastern University will develop a qualitatively and quantitatively reliable quantum mechanical method and an automated embedded correlated wavefunction (AutoECW) theory for kinetic modeling in heterogeneous catalysis. This project aims to develop and implement AutoECW to eliminate two bottlenecks in standard embedded correlated wavefunction (ECW) theory, requiring specialized expertise and high computational cost to accelerate the mainstream use of this theory in computational heterogeneous catalysis. Using ammonia electrosynthesis as an example, this project seeks to re-elucidate reaction mechanisms by performing microkinetic modeling of the electrochemical nitrogen reduction reaction (NRR) with metal catalysts using the developed AutoECW. Improvements in fundamental understanding have the potential to inspire new design principles and descriptors for ammonia electrosynthesis toward the goal of discovering novel catalysts with improved activity and selectivity. AutoECW aims to enable proper simulations of many compelling systems within heterogeneous catalysis that are difficult to model with conventional density functional theory.