Geometric landscapes for material discovery within energy-structure-function maps.

Chemical Science
Seyed Mohamad MoosaviBerend Smit

Abstract

Porous molecular crystals are an emerging class of porous materials formed by crystallisation of molecules with weak intermolecular interactions, which distinguishes them from extended nanoporous materials like metal-organic frameworks (MOFs). To aid discovery of porous molecular crystals for desired applications, energy-structure-function (ESF) maps were developed that combine a priori prediction of both the crystal structure and its functional properties. However, it is a challenge to represent the high-dimensional structural and functional landscapes of an ESF map and to identify energetically favourable and functionally interesting polymorphs among the 1000s to 10 000s of structures typically on a single ESF map. Here, we introduce geometric landscapes, a representation for ESF maps based on geometric similarity, quantified by persistent homology. We show that this representation allows the exploration of complex ESF maps, automatically pinpointing interesting crystalline phases available to the molecule. Furthermore, we show that geometric landscapes can serve as an accountable descriptor for porous materials to predict their performance for gas adsorption applications. A machine learning model trained using this geometric...Continue Reading

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Citations

Jun 11, 2020·Chemical Reviews·Kevin Maik JablonkaBerend Smit
Mar 2, 2021·The Journal of Physical Chemistry Letters·Eun Hyun Cho, Li-Chiang Lin
Aug 15, 2020·Nature Communications·Seyed Mohamad MoosaviHeather J Kulik
Aug 11, 2021·Chemical Reviews·Amir H FarmahiniLev Sarkisov
Nov 11, 2020·Journal of the American Chemical Society·Seyed Mohamad MoosaviBerend Smit

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Methods Mentioned

BETA
MDS

Software Mentioned

DMACRYS
atomic simulation environment ( ASE )
learn
Zeo
scikit
DScribe

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