Collaborative Research: CDS&E: Controlling encapsulated site microenvironments of metal nanocluster catalysts for nitrogen-based hydrogen carrier chemistries

About This Grant

Small metal nanoparticles are commonly used as materials to accelerate chemical reactions of importance, such as the production and use of fuels and chemicals. However, it is difficult to control the structures of these nanoparticles and how molecules interact with their surfaces. This limits the ability to control and tune their performance. This project will develop computational approaches to examine metal clusters within tiny, ordered pores of aluminosilicate materials called zeolites. The work will combine computer simulations and machine learning to understand how these clusters are formed, and how they change during reaction processes. By changing the relative size of the zeolite pore and metal cluster size, the project will understand how nanometer-scale confinement impacts metal clusters and influences their catalytic reactivity. This will allow the researchers to design materials to perform chemical reactions with lower energy inputs, particularly for reactions that use liquid molecules to store and transport hydrogen. Educational and outreach efforts will train undergraduate and graduate students in new machine learning techniques and engage high school students with direct scientific programs. The public will be engaged through catalysis simulation tools and applications developed to introduce students to model-driven scientific discovery. This project focuses on designing metal nanoclusters encapsulated in nanoporous aluminosilicates where precise control over catalysts microenvironment will allow the team to optimize electronic and steric interactions to promote (de)hydrogenation chemistries. This project will use theory and simulation to predict the most promising carrier / zeolite pairs with machine learning tools. In particular, the project will seek to understand and control X-H bond dissociation steps (X = C, N) in the dehydrogenation of ammonia and N-heterocyclic organic molecules over zeolite-encapsulated noble metal nanoclusters. The project will develop computational models that reflect the kinetically relevant chemical interactions and nanocluster structures under reaction conditions. This project will directly lead to short- and long-term translational benefits to fundamental catalysis science and technological advances for designing selective and stable nanocluster catalysts. 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.