Computationally-guided crystalline materials discovery

We use computational methods to design targeted functionality into organic solids by understanding and predicting the underlying molecular assembly processes. We are closely integrating computation and experiment to discover new molecular crystals.

Synthesis of porous organic cage molecules

Our group is interested in the synthesis of porous organic cage molecules, which are characterized by well-defined, hollow structures. These cages are highly versatile and can be used in various applications, including molecular encapsulation, drug delivery, and as components in advanced materials.

Through a collaboration with Professor Kim Jelfs (Imperial), we have been able to predict the self-assembly behaviour of these molecules, leading to the synthesis of cages with precisely controlled pore sizes and shapes. We have also incorporated cage-like building blocks into different classes of materials, recently reporting cage-HOF and -COF materials as well as a cage-of-cages.

Selected key publications

Non-metal organic frameworks (NMOFs)

In addition to our work on porous organic cages, we have recently reported a new class of framework materials which we call Non-Metal Organic Frameworks (NMOFs). NMOFs are obtained by inverting the design pattern of traditional MOFs, exploiting the electrostatic interaction between negatively charged non-metal nodes and cationic organic linkers. Our research has focused on designing and synthesizing these frameworks, which has opened up new possibilities for applications in gas storage, separation, and catalysis.

Selected key publications

Collaboration with computational chemists

A key aspect of our success in this area has been our collaboration with computational chemists, particularly Professor Graeme Day at the University of Southampton. A significant challenge in the design of NMOFs is the lack of directionality in the electrostatic interactions which maintain the open pore structure, making reticular design principles difficult to apply. By utilising computational predictions, we have been able to identify promising candidate linker molecules for synthesis, thereby streamlining the discovery process. This approach allows us to predict the structures and properties of NMOFs before they are synthesized, saving time and resources.

The computational models developed by Professor Day's team have been instrumental in guiding our experimental efforts, resulting in the successful creation of several novel NMOFs with exceptional performance characteristics. These interdisciplinary efforts underscore the synergistic potential of combining experimental and computational expertise in materials discovery, leading to breakthroughs that push the boundaries of what is possible in the design and application of advanced materials.