Zeolites are a class of crystalline, solid materials that contain pores of the size of molecules, lending to their wide use in applications such as gasoline refining, and cleaning exhaust coming from diesel vehicles. Zeolites are naturally occurring, but technological materials are produced synthetically and at large scale. The properties of a particular zeolite are determined in part by its pore size and shape, and in part by the chemical elements in the material; however, specifics of these relationships are poorly understood. As a result, nominally the same zeolites may show vastly different performance in a given application. The overarching aim of this project is to develop computer models and experimental protocols that increase our ability to precisely locate the positions of elements within the zeolite pores during the zeolite synthesis process. This understanding is expected to lead to materials that have superior performance in current applications, are longer-lasting and more durable, and can perform functions that are not possible today. To achieve these ends, it brings together a team of researchers with expertise in zeolite synthesis and characterization, in experiment and in molecular-scale computer models, and from industrial and academic laboratories. It delivers new modeling protocols and new materials, while simultaneously training students in a diverse, collaborative environment who are well prepared for careers in chemical technologies.
The project focuses in particular on crystalline aluminosilicate zeolites. In these materials, aluminum heteroatoms within the zeolite framework are anionic charge centers. Increasing evidence indicates that the relative proximity of these aluminum centers has a significant impact on the ultimate properties of the zeolite, in particular in their function in Bronsted acid catalysis (methanol dehydration) and in redox catalysis (the selective catalytic reduction of NOx). The main hypotheses are cationically charged structure-directing agents (SDAs) present during the synthesis process have a determining effect on the location of those Al atoms within a given zeolite lattice, their effect can be inferred from the interactions between SDAs and the pre-formed, aluminum-substituted zeolite, and the same modeling approach can be used to predict speciation during post-synthetic ion exchange. To test these hypotheses, the project develops classical and first-principles models to predict zeolite compositional phase diagrams for organic SDAs and inorganic cations vs silicon-to-aluminum ratio in a series of zeolite frameworks. These models are validated against experimental observation on laboratory-synthesized zeolites, using both ex situ spectroscopic and chemical characterization as well kinetic evaluations under catalytic conditions, and informed by first-principles and microkinetic modeling predictions of the relationship between Al atom location and properties. The project advances the computational design of zeolite materials in the context of practically significant catalytic reactions in a computation/experiment and academic/industrial collaborative setting.
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.
