Quantifying similarity of pore-geometry in nanoporous materials

Yongjin Lee; Senja D. Barthel; Paweł Dłotko; S. Mohamad Moosavi; Kathryn Hess; Berend Smit

doi:10.1038/ncomms15396

Quantifying similarity of pore-geometry in nanoporous materials

Yongjin Lee, Senja D. Barthel, Paweł Dłotko, S. Mohamad Moosavi, Kathryn Hess, Berend Smit^*

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

In most applications of nanoporous materials the pore structure is as important as the chemical composition as a determinant of performance. For example, one can alter performance in applications like carbon capture or methane storage by orders of magnitude by only modifying the pore structure. For these applications it is therefore important to identify the optimal pore geometry and use this information to find similar materials. However, the mathematical language and tools to identify materials with similar pore structures, but different composition, has been lacking. We develop a pore recognition approach to quantify similarity of pore structures and classify them using topological data analysis. This allows us to identify materials with similar pore geometries, and to screen for materials that are similar to given top-performing structures. Using methane storage as a case study, we also show that materials can be divided into topologically distinct classes requiring different optimization strategies.

Original language	English
Article number	15396
Journal	Nature Communications
Volume	8
DOIs	https://doi.org/10.1038/ncomms15396
Publication status	Published - 23 May 2017
Externally published	Yes

Funding

During the early stage of the research Y.L. and B.S. were supported by the Center for Gas Separations Relevant to Clean Energy Technologies, an Energy Frontier Research Center funded by the DOE, Office of Science, Office of Basic Energy Sciences under award DE-SC0001015. Y.L. (during the later stages of the research) and S.B. were supported by the National Center of Competence in Research (NCCR) 'Materials' Revolution: Computational Design and Discovery of Novel Materials (MARVEL)' of the Swiss National Science Foundation (SNSF). M.M. was supported by the Deutsche Forschungsgemeinschaft (DFG, priority program SPP 1570). B.S. was supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 666983) and by the 'Korean-Swiss Science and Technology Programme' (KSSTP) grant number 162130 of the Swiss National Science Foundation (SNSF). P.D. was supported by the Advanced Grant of the European Research Council GUDHI, (Geometric Understanding in Higher Dimensions) (grant agreement No 339025).

Funders	Funder number
European Research Council GUDHI
KSSTP
U.S. Department of Energy
Office of Science
Basic Energy Sciences	DE-SC0001015
Seventh Framework Programme	666983, 339025
nccr – on the move
European Research Council
Deutsche Forschungsgemeinschaft
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung	162130
Horizon 2020

Keywords

nonporous materials
persistent homology
descriptors
topological data analysis

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AU - Hess, Kathryn

AU - Smit, Berend

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Quantifying similarity of pore-geometry in nanoporous materials

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High-Throughput Screening Approach for Nanoporous Materials Genome Using Topological Data Analysis: Application to Zeolites

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