Startseite High-throughput assessment of hypothetical zeolite materials for their synthesizeability and industrial deployability
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High-throughput assessment of hypothetical zeolite materials for their synthesizeability and industrial deployability

  • Jose Luis Salcedo Perez , Maciej Haranczyk und Nils Edvin Richard Zimmermann EMAIL logo
Veröffentlicht/Copyright: 25. März 2019

Abstract

Zeolites are important microporous framework materials, where 200+ structures are known to exist and many millions so-called hypothetical materials can be computationally created. Here, we screen the “Deem” database of hypothetical zeolite structures to find experimentally feasible and industrially relevant materials. We use established and existing criteria and structure descriptors (lattice energy, local interatomic distances, TTT angles), and we develop new criteria which are based on 5-th neighbor distances to T-atoms, tetrahedral order parameters (or, tetrahedrality), and porosity and channel dimensionality. Our filter funnel for screening the most attractive zeolite materials that we construct consists of nine different types of criteria and a total of 53 subcriteria. The funnel reduces the pool of candidate materials from initially >300,000 to 70 and 33, respectively, depending on the channel dimensionality constraint applied (2- and 3-dimensional vs. only 3-dimensional channels). We find that it is critically important to define longer range and more stringent criteria such as the new 5-th neighbor distances to T-atoms and the tetrahedrality descriptor in order to succeed in reducing the huge pool of candidates to a manageable number. Apart from four experimentally achieved structures (BEC, BOG, ISV, SSF), all other candidates are hypothetical frameworks, thus, representing most valuable targets for synthesis and application. Detailed analysis of the screening data allowed us to also propose an exciting future direction how such screening studies as ours could be improved and how framework generating algorithms could be competitively optimized.


Corresponding author: Dr. Nils Edvin Richard Zimmermann, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, 94720 Berkeley, USA

Acknowledgments

This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences and Biosciences Division, as part of the Computational Chemical Sciences Program, and within the Nanoporous Materials Genome Center (DE-FG02-17ER16362). This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231.

  1. Supporting information available: List of the 215 IZA structures analysed and used for criterion definition in this work as well as our top 70 hypothetical zeolite can- didates from Deem’s database and results from a slightly different filter funnel. Furthermore, we provide a list of symbols and acronyms and abbreviations.

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/zkri-2018-2155).


Received: 2018-12-02
Accepted: 2019-02-25
Published Online: 2019-03-25
Published in Print: 2019-07-26

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