Reaction Monitoring and Structural Characterisation of Coordination Driven Self-Assembled Systems by Ion Mobility-Mass Spectrometry

Can you envisage a world where building a new catalyst or an artificial enzyme is like following an architectural plan for building a house? This is difficult as we don't even fully understand the construction materials! We research the properties of molecular building-blocks and their "constructed" aggregates, towards drawing up these type of blueprints.

We use high resolution ion-mobility spectrometry and mass spectrometry, computational chemistry, combinatorial libraries and robotics; along with wet chemistry to understand structure and function. We are targeting many types of chemistry involving metal ions. The way we are currently using these techniques is unique.

Electrospray ionization-mass spectrometry (ESI-MS) is rapid, sensitive, precise and well-controlled. Ion mobility (IMS) separates much quicker than chromatographic techniques, in milliseconds rather than minutes or hours. It is ideal for measuring the size and shape of molecules and complexes.[1] It also seamlessly interfaces with mass spectrometry. We use these methods together to monitor target reactions, both simple and complex, with ease.

We are interested in structure, structure-function relationships, mechanism, theory underpinning chemical reactions and catalysis, chemical data crunching, and methodological development for mass spectrometry and ion-mobility. We are particularly interested in the way metals, ligands and organic molecules aggregate or react.

Dynamic combinatorial libraries (DCL) are self-assembling components in equilibrium. Depending on the ligand elbow different shaped oligomers are possible. DCL allow a high throughput screening for useful shaped molecules. Many can lead to useful supramolecules. In this project, robotically generated DCLs using diketonate ligands will be monitored for the stoichiometry & shape of the evolving molecular assemblies. We will push the reactions in different ways, using additives and other changes to solution conditions. We are working towards fully automating the functional material discovery process using high throughput experiments, machine learning and computational chemistry.[2] This project sits in a multidisciplinary space of supramolecular chemistry using digital methods to understand unique chemistry.

Interested prospective candidates are highly encouraged to discuss their research interests with Dr Rijs.