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Imagine having a library containing 3 million books, but no way to search for the one you needed. Researchers frequently report new nanoporous materials, with a wide array of potential applications, chemical properties, and pore geometries.
Databases of synthesized and predicted nanoporous materials are available, however, until now the only method of finding a nanoporous material with a desired overall pore geometry was by visual inspection. In recent years, the number of nanoporous materials reported has grown exponentially so finding structures by visual inspection has become less and less feasible.
Researchers from the Chemical Engineering and Mathematics departments at Ecole Polytechnique Fédérale de Lausanne (EPFL) have collaborated to develop a method capable of comparing material pore structures, making it possible to search databases of nanoporous materials to find candidates with a desired pore structure.
The method was recently reported in Nature Communications and involves quantifying the geometric similarity of pore structures using a mathematical technique known as persistent homology, commonly used in facial recognition software. The method generates “fingerprints” that characterize the pore structure of a material and can be compared to find similar structures in a database quickly and easily.
Berend Smit, the lead researcher on the study, described the method “While humans are intuitively good at recognizing shapes as the same or different, we needed to work with the math department at EPFL to develop a formalism that can teach this skill to a computer."
This is one of the first examples of persistent homology requiring analysis in three dimensions. "In the field of algebraic topology, mathematicians have formulated the theory of persistence homology in any dimension," says Kathryn Hess, a mathematician at EPFL. "Previous applications used only the first two of these dimensions, so it's exciting that chemical engineers at EPFL have discovered a significant application that requires the third dimension as well."
Nanoporous materials find an array of applications including gas separation, gas storage, and catalysis. They can have various chemical compositions and include materials like zeolites, metal organic frameworks, and porous polymer networks, but they all have pores in the range of 0.2-1000 nm in their 3D structures.
The presence of nanopores results in absorption and catalytic properties, but the specific properties of a given nanoporous material depend on the size and shape of the nanopores.
The team tested their new method by searching for nanoporous materials with similar pore structures to those widely used in methane storage. The method was able to find nanoporous materials with similar pore structures that performed as well as the known materials for methane storage.
They also found distinct groups of materials with different pore structures that worked well for methane storage (Figure 1), with each family of materials requiring a different optimization strategy.
Currently, the method has only been applied to gas absorption, where the materials are chemically passive and only provide adsorption sites for the gas.
For applications like catalysis, where the material must also provide the correct chemical properties, the team suggests that the methodology could be extended to include properties such as chemical specificity and charge distribution. Once optimized, the method could help researchers to identify promising candidates for their application quickly and easily.
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Sources:
https://www.sciencedaily.com/releases/2017/05/170523082012.htm Accessed May 30th, 2017.
Lee Y, Barthel SD, Dłotko P, Mohamad Moosavi S, Hess K, Smit B, Quantifying similarity of pore-geometry in nanoporous materials. Nat. Commun. 8:15396, 2017.
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