Zeolites are versatile materials for heterogeneous catalysis due to their large topological and compositional diversity. Although this diversity allows tailoring a zeolite towards chemical reactions, phase competition between polymorphs often hinders the crystallization of a single zeolite framework. Computational methods can aid zeolite synthesis by proposing organic structure-directing agents (OSDAs) that template desired structures. However, most simulations are performed for one framework at a time, and cannot predict whether OSDAs are more likely to synthesize another polymorph instead of the targeted one. Consequently, computer-made templates often fail to crystallize the zeolites they were designed for. Here, we propose a first-principles approach to control zeolite phase selectivity using high-throughput simulations. We start developing algorithms that accelerate zeolite-OSDA simulations by two orders of magnitude compared to existing methods. Then, we calculate more than half a million host-guest pairs, from which we compute binding affinity metrics that rationalize phase competition in zeolites. The metrics explain synthesis outcomes from more than one thousand articles extracted from the literature and enable the design of selective, chemically simple OSDAs. Experimental results show that the proposed templates additionally enhance the catalytic properties of the obtained frameworks, which outperform state-of-the-art catalysts in methanol-to-oleofin reactions. Finally, we predict and realize an intergrowth using a single bi-selective OSDA, thus imprinting reaction selectivities to the resulting structure by tuning phase competition. This work offers a platform for controlling zeolite synthesis and catalytic properties through polymorphism engineering.

First principles control of zeolite phase competition and intergrowth with high-throughput simulations

ACS Fall 2021

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