(6gk) Understanding and Predicting the Activity of Zeolite Catalysts | AIChE

(6gk) Understanding and Predicting the Activity of Zeolite Catalysts


Zeolites are the most important industrial catalysts today. Their main application in catalysis is within crude oil refinement, but more recently they have been shown to be very effective systems in the reforming of biomass and in cleaning car exhaust gases. The activity for a given process is determined by the framework type and by the preparation of the catalyst. Similar to quartz, zeolites are mainly composed of Si and O. Exchanging SiIV by e.g. AlIII creates a local charge imbalance, which in turn is compensated by a counter ion. These ions act as catalytically active centers. The activity of the catalyst will depend on the distribution of these active sites, which in turn is determined by the distribution of Al framework atoms.

The goal in my research is to characterize this underlying distribution, to show how it can be used to understand the catalytic behavior of zeolite catalysts, and, in a next step, to computationally predict this distribution and design optimal catalysts.

One of the largest challenges in characterizing zeolite catalysts is the mismatch between the calculated spectra, which are typically modeled statically and correspond to experimental conditions of 0K, and experimental measurements at ambient conditions. Therefore the goal is to develop and apply theoretical, ensemble based methods that are comparable to experimental conditions. This includes the use of molecular dynamics simulations, distribution based techniques and Monte-Carlo simulations to calculate e.g. IR, NMR- and UV-vis spectra as well as studying the impact of water under the given conditions on the catalyst.

Another key point is to understand the impact of this distribution on the catalytic activity. This can be as simple as comparing catalytic activity measurements to the distribution of active sites in the material, but can also be highly complicated when the positioning of the active sites influences their chemical activity or changes the influence of the framework on the reaction. These confinement effects have been a major direction within recent research in the field and will also play a key role in my future research.

With the increase in computational power approaches to predict possible new catalysts have become more and more important. The mid- to long-term goal in my research is to develop a screening based approach to design zeolite catalysts. Based upon the ideas described in the previous paragraph it is therefore necessary to identify descriptors for chemical influence of the active sites and the zeolite framework. The second step is to screen various zeolite structures for these parameters, which in the end will lead to potential candidates for the reactions in question. This includes understanding the errors of theory by comparing with experiment to arrive at a quantitatively accurate approach.


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