Data-Driven Design of Biselective Templates for Intergrowth Zeolites
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data-driven-design-of-bi-selective-osd-as-for-intergrowth-zeolites.pdf
Description
Submitted version
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411.79 KB
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Author(s) • • • •
Schwalbe-Koda, Daniel
Corma, Avelino
Román-Leshkov, Yuriy
Moliner, Manuel
Gómez-Bombarelli, Rafael
Date Issued
2021
Journal
Journal of Physical Chemistry Letters
Publisher
American Chemical Society (ACS)
Citation
Schwalbe-Koda, Daniel, Corma, Avelino, Román-Leshkov, Yuriy, Moliner, Manuel and Gómez-Bombarelli, Rafael. 2021. "Data-Driven Design of Biselective Templates for Intergrowth Zeolites." Journal of Physical Chemistry Letters, 12 (43).
Version
Original manuscript
Abstract
Zeolites are inorganic materials with wide industrial applications due to their topological diversity. Tailoring confinement effects in zeolite pores, for instance by crystallizing intergrown frameworks, can improve their catalytic and transport properties, but controlling zeolite crystallization often relies on heuristics. In this work, we use computational simulations and data mining to design organic structure-directing agents (OSDAs) to favor the synthesis of intergrown zeolites. First, we propose design principles to identify OSDAs which are selective toward both end members of the disordered structure. Then, we mine a database of hundreds of thousands of zeolite-OSDA pairs and downselect OSDA candidates to synthesize known intergrowth zeolites such as CHA/AFX, MTT/TON, and BEC/ISV. The computationally designed OSDAs balance phase competition metrics and shape selectivity toward the frameworks, thus bypassing expensive dual-OSDA approaches typically used in the synthesis of intergrowths. Finally, we propose potential OSDAs to obtain hypothesized disordered frameworks such as AEI/SAV. This work may accelerate zeolite discovery through data-driven synthesis optimization and design.
MIT Department
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Department of Chemical Engineering
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Attribution-NonCommercial-ShareAlike 4.0 International
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DOI of Published Version
https://doi.org/10.1021/ACS.JPCLETT.1C03132