CAREER: Engineering Active Site Structure for Selective Nitrogen Catalysis

Nitrate pollution from agricultural runoff and industrial wastewater has been linked to significant human health concerns, such as birth defects and cancer, and environmental impacts, such as algae blooms. This project will focus on developing catalysts to convert nitrate to inert nitrogen gas or ammonia for reuse in fertilizers. In particular, this project will seek to understand how the atomic-scale details of catalyst structure and composition can control the selectivity between these possible reaction products in electrocatalytic transformations.

The outcomes of this project will provide critical strategies and technological advancement for nitrogen cycle remediation in wastewater streams. The knowledge gained will also influence broader understanding of the role of catalyst structural details in governing the formation of reaction products. The research objectives of this project are integrated with an education plan that will drive excitement for computational materials design in rural communities as well as in undergraduate chemical engineering coursework.

This project seeks to understand the detailed effects of local catalyst structural features in controlling the reactivity and selectivity of transformations on nanoparticle catalysts. Computational modeling on realistic nanoparticles is limited by the high computational cost of such models along with the myriad possible active sites that can be generated by an evolving nanoparticle.

This research is founded upon a structure-sensitive modeling approach that utilizes local structural descriptors to predict the energetics of elementary reaction steps based on the stability of the local binding site. This framework simultaneously enables an investigation of active site and catalyst restructuring, identifying features likely to form under reaction conditions.

This project will apply density functional theory calculations to establish correlations between catalyst structure and the activation energies of elementary reaction steps in electrocatalytic nitrate reduction on disordered surface geometries; it is hypothesized that manipulating the local coordination environment of a bifunctional silver-based catalyst can tune reaction selectivity between dinitrogen and ammonia. This project will seek a self-consistent description of reaction energetics by incorporating data science toolkits to describe interactions between adsorbed reactive species, enabling spatially-resolved kinetic Monte Carlo simulations of reactivity on representative nanoparticle models.

This framework will be applied to understand the effects of catalyst support and nitrate reduction intermediates on the reconstruction of silver-based bimetallic catalysts under reaction conditions, enabling a holistic simulation of catalyst activity, selectivity, and stability. The fundamental knowledge obtained in this study will provide key mechanistic insights into nitrogen cycle chemistry and inform the design of selective electrocatalytic transformations.

The educational objectives of this research will train and inspire the next generation of innovators, focusing on deployment of STEM outreach efforts to rural communities. A new outreach activity will allow students to participate in the hands-on design of catalysts using toy construction kits to build models that are scanned and analyzed using the research-based model to predict the reactivity and selectivity of the exposed geometric features.

This activity will augment the science toolkits of both rural middle school students and their educators, with further extension into core undergraduate numerical methods coursework. Together, these initiatives will foster excitement in the next generation of scientists for the role of computations in driving innovation for sustainable chemical transformations.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.