<i>In silico</i>design and assembly of cage molecules into porous molecular materials

Bernabei, Marco; Pérez‐Soto, Raúl; García, Ismael Gómez; Harańczyk, Maciej

doi:10.1039/c8me00055g

Cited by 11 publications

(7 citation statements)

References 38 publications

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“…The presented contributions can be integrated with highthroughput discovery workflows for porous molecular materials 43 as well as employed in detail for characterization of particular porous molecules of interest.…”

Section: Discussionmentioning

confidence: 99%

Toward Automated Tools for Characterization of Molecular Porosity

García

Bernabei

Harańczyk

2018

J. Chem. Theory Comput.

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The emerging advanced porous materials, e.g. extended framework materials and porous molecular materials, offer an unprecedented level of control of their structure and function. The enormous possibilities for tuning these materials by changing their building blocks mean that, in principle, optimally performing materials for a variety of applications can be systematically designed. However, the process of finding a set of optimal structures for a given application requires computational high-throughput tools to analyze and sieve through many candidate materials. In particular, in the case of porous molecular materials, the analysis and selection of a molecule is one of the key aspects as the structure of the molecule determines the structure of the resulting material, and very often the porosity of the molecule significantly contributes to the porous properties of the resulting material. In this work, we introduce definitions and algorithms to characterize porosity at the molecular level, along with a software implementation of these algorithms. We demonstrate applications of the software tool in the discovery and characterization of porous molecules among ca. 94 million molecules currently enlisted in the PubChem database.

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Section: Discussionmentioning

confidence: 99%

Toward Automated Tools for Characterization of Molecular Porosity

García

Bernabei

Harańczyk

2018

J. Chem. Theory Comput.

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“…CSP has been used in porous molecular systems to correctly predict the experimentallyobserved crystal structure, [42] preference for enantiopure or racemic packing, [42] pore-size, [43] as well as identifying a priori the most promising molecules for targeted synthesis of properties via energy-structure-function maps. [44][45][46] We recently combined the whole workflow of structure prediction, from reaction outcome, molecular structure to crystal packing for the first time. [47] With a computational model of the molecular or solid-state structure, it is then possible to perform a variety of calculations to determine the properties of the material, such as poretopology, surface area, guest uptake and selectivity.…”

Section: Kim Jelfs Is a Senior Lecturer And Royal Societymentioning

confidence: 99%

High‐Throughput Approaches for the Discovery of Supramolecular Organic Cages

Greenaway

Jelfs

2020

ChemPlusChem

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The assembly of complex molecules, such as organic cages, can be achieved through supramolecular and dynamic covalent strategies. Their use in a range of applications has been demonstrated, including gas uptake, molecular separations, and in catalysis. However, the targeted design and synthesis of new species for particular applications is challenging, particularly as the systems become more complex. High‐throughput computation‐only and experiment‐only approaches have been developed to streamline the discovery process, although are still not widely implemented. Additionally, combined hybrid workflows can dramatically accelerate the discovery process and lead to the serendipitous discovery and rationalisation of new supramolecular assemblies that would not have been designed based on intuition alone. This Minireview focuses on the advances in high‐throughput approaches that have been developed and applied in the discovery of supramolecular organic cages.

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“…This is valuable because the synthesis and characterization of a new molecule can often take many months in the laboratory. In recent years, advances in computational modelling have enabled the reliable design and prediction of the formation of organic cages, including the topology most likely to be formed by synthesis and the subsequent crystal structure packing, including preferences for forming racemic or enantiopure forms . However, a priori computational design becomes increasingly complicated when the number of distinct components increases because of the potential to form different self‐assembled competing products.…”

Section: Introductionmentioning

confidence: 99%

From Concept to Crystals via Prediction: Multi‐Component Organic Cage Pots by Social Self‐Sorting

et al. 2019

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We describe the a priori computational prediction and realization of multi‐component cage pots, starting with molecular predictions based on candidate precursors through to crystal structure prediction and synthesis using robotic screening. The molecules were formed by the social self‐sorting of a tri‐topic aldehyde with both a tri‐topic amine and di‐topic amine, without using orthogonal reactivity or precursors of the same topicity. Crystal structure prediction suggested a rich polymorphic landscape, where there was an overall preference for chiral recognition to form heterochiral rather than homochiral packings, with heterochiral pairs being more likely to pack window‐to‐window to form two‐component capsules. These crystal packing preferences were then observed in experimental crystal structures.

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In silicodesign and assembly of cage molecules into porous molecular materials

Abstract: Design and assembly of cage molecules into new highly-porous molecular crystals.

Cited by 11 publications

References 38 publications

Toward Automated Tools for Characterization of Molecular Porosity

Toward Automated Tools for Characterization of Molecular Porosity

High‐Throughput Approaches for the Discovery of Supramolecular Organic Cages

From Concept to Crystals via Prediction: Multi‐Component Organic Cage Pots by Social Self‐Sorting

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