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Supramolecular Recognition in Crystalline Nanocavities through Monte Carlo and Voronoi Network Algorithms

Daniel Schwalbe‐Koda, Rafael Gómez‐Bombarelli

2021The Journal of Physical Chemistry C29 citationsDOIOpen Access PDF

Abstract

Computational screening of templating molecules enables the discovery of new synthesis routes for zeolites. Despite decades of work in molecular modeling of organic structure-directing agents (OSDAs), the development and benchmarking of algorithms for docking molecules in nanoporous materials has received scarce attention. Here, we introduce Voronoi Organic–Inorganic Docker (VOID), a method based on Voronoi diagrams to dock molecules in crystalline materials, and release it as a Python package. Benchmarks of the implementation show that it generates docked poses up to 95 times faster than the traditional Monte Carlo docking scheme. We then evaluate the algorithm by obtaining binding energies for about 120 zeolite–OSDA pairs of industrial relevance. The computed host–guest interactions qualitatively explain experimental outcomes for traditional synthesis routes from the literature. The results further suggest new OSDAs to synthesize known zeolites. Finally, we exemplify the generality of VOID by docking molecules inside a metal–organic framework and on a metal surface. The proposed method and software provide a low-cost computational approach for generating molecule–material interfaces.

Topics & Concepts

Voronoi diagramNanoporousMonte Carlo methodComputer sciencePython (programming language)Docking (animal)Computational scienceSupramolecular chemistryMoleculeMaterials scienceNanotechnologyAlgorithmChemistryGeometryMathematicsOrganic chemistryMedicineStatisticsNursingOperating systemZeolite Catalysis and SynthesisMetal-Organic Frameworks: Synthesis and ApplicationsMachine Learning in Materials Science
Supramolecular Recognition in Crystalline Nanocavities through Monte Carlo and Voronoi Network Algorithms | Litcius