Computational modelling and topological design of porous organic cages
File(s)
Author(s)
Santolini, Valentina
Type
Thesis
Abstract
Porous organic cages are a class of materials constructed by intermolecular packing of discrete organic molecules, that contain void space in an internal cavity, and are typically solution processable. Many experimental and computational studies have been conducted on porous cages, however design and prediction of new molecular structures still represents a great theoretical challenge.
During my PhD, I developed a computational strategy to generate new porous organic molecules and test their experimental feasibility. An automated pipeline assembles building blocks with different numbers of reactive ends into cages with the underlying topology of geometric polyhedra. The topologies are defined and classified according to a new nomenclature, which is based on the topicity of the precursors contained in each cage. Once multiple topologies are generated from a pair of precursors, the geometry and energy of each molecule are investigated to understand which structure is the most experimentally likely to form. The structures that do not retain a cavity are “inflated” with a constrained molecular dynamics technique that simulate the scaffolding effect of the solvent, which is otherwise not taken into account.
The prediction strategy has been successfully tested on a number of experimentally available structures, and on a wide range of novel organic cages in the context of a computational-experimental collaboration with the group of Prof. A. Cooper (University of Liverpool). The experimental part was carried out by the Cooper’s group, who used a high-throughput screening platform to carry out the synthesis of 78 new cages, starting from a selection of different functional precursors mixed in a combinatorial way. I carried out the computational part of the project, which was dedicated to the prediction of the same cages, and results were compared to rationalise the criteria for optimal design of porous organic cages. The pipeline can be now integrated with crystal structure prediction methods to suggest promising novel porous organic materials for the synthesis.
During my PhD, I developed a computational strategy to generate new porous organic molecules and test their experimental feasibility. An automated pipeline assembles building blocks with different numbers of reactive ends into cages with the underlying topology of geometric polyhedra. The topologies are defined and classified according to a new nomenclature, which is based on the topicity of the precursors contained in each cage. Once multiple topologies are generated from a pair of precursors, the geometry and energy of each molecule are investigated to understand which structure is the most experimentally likely to form. The structures that do not retain a cavity are “inflated” with a constrained molecular dynamics technique that simulate the scaffolding effect of the solvent, which is otherwise not taken into account.
The prediction strategy has been successfully tested on a number of experimentally available structures, and on a wide range of novel organic cages in the context of a computational-experimental collaboration with the group of Prof. A. Cooper (University of Liverpool). The experimental part was carried out by the Cooper’s group, who used a high-throughput screening platform to carry out the synthesis of 78 new cages, starting from a selection of different functional precursors mixed in a combinatorial way. I carried out the computational part of the project, which was dedicated to the prediction of the same cages, and results were compared to rationalise the criteria for optimal design of porous organic cages. The pipeline can be now integrated with crystal structure prediction methods to suggest promising novel porous organic materials for the synthesis.
Version
Open Access
Date Issued
2018-03
Date Awarded
2018-06
Advisor
Jelfs, Kim
Harrison, Nicholas
Publisher Department
Chemistry
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)