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Barcodes for nanoporous materials

Yongjin Lee1, Senja D. Barthel1, Paweł Dłotko2, S. Mohamad Moosavi1, Kathryn Hess3, Berend Smit1*

1 Laboratory of Molecular Simulation, EPFL, Switzerland

2 DataShape Group, Inria Saclay, France

3 UPHESS, EPFL, Switzerland

* Corresponding authors emails: berend.smit@epfl.ch
DOI10.24435/materialscloud:2017.0001/v1 [version v1]

Publication date: Mar 14, 2017

How to cite this record

Yongjin Lee, Senja D. Barthel, Paweł Dłotko, S. Mohamad Moosavi, Kathryn Hess, Berend Smit, Barcodes for nanoporous materials, Materials Cloud Archive 2017.0001/v1 (2017), doi: 10.24435/materialscloud:2017.0001/v1.


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. Recently, we developed a pore recognition approach to quantify similarity of pore structures using topological data analysis. Barcodes generated with using this approach allow us to identify materials with similar pore geometries, and to screen for materials that are similar to given top-performing structures. This database has barcodes for zeolites, metal organic frameworks, and zeolitic imidazolate frameworks.

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File name Size Description
839.2 MiB Barcodes for metal organic frameworks and zeolitic imidazolate frameworks
121.7 MiB Barcodes for zeolites


Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Journal reference (Paper in which the data is published)
Y. Lee, S. D. Barthel, P. Dłotko, S. M. Moosavi, K. Hess, B. Smit, “Quantifying similarity of pore-geometry in nanoporous materials”, Nature Communications, 8:15396 (2017) doi:10.1038/ncomms15396


zeolites metal organic frameworks nanoporous materials topological data analysis persistence homology MARVEL

Version history:

2017.0001/v1 (version v1) [This version] Mar 14, 2017 DOI10.24435/materialscloud:2017.0001/v1