Barcodes for nanoporous materials

Authors: 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 author email:

DOI10.24435/materialscloud:2017.0001/v1 (version v1, submitted on 14 March 2017)

How to cite this entry

Yongjin Lee, Senja D. Barthel, Paweł Dłotko, S. Mohamad Moosavi, Kathryn Hess, Berend Smit, Barcodes for nanoporous materials, Materials Cloud Archive (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.

Materials Cloud sections using this data

No Explore or Discover sections associated with this archive entry.


File name Size Description
MD5MD5: ec5cc3ff838342f74bf902064109cbcd
839.2 MiB Barcodes for metal organic frameworks and zeolitic imidazolate frameworks
MD5MD5: 146d7965da17866d21a429b4929da1c1
121.7 MiB Barcodes for zeolites


Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.

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

14 March 2017 [This version]