Improving Condensed Phase Simulations to Predict Reaction Outcomes

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This project aims to pair theory and experiment to develop computational models to improve the description of solvent effects. This knowledge is crucial because most real-world reactions occur in the solution phase, yet existing models are limited due to the very large errors involved. The intended outcome is to develop methods to overcome these limitations and expand the utility of such models to predict reaction outcomes. These methods will transform traditional trial-and-error approaches to synthesis to rational, computation-driven design of chemical reagents and catalysts, along with the ability to rationally optimise reaction conditions.

This project will combine aspects of both computational and experimental physical organic chemistry and will therefore suit someone with an interest in both. Importantly, the balance of these two components can be tailored to the interests of the candidate.

The ideal candidate should have a strong background in undergraduate physical and organic chemistry. More importantly, the candidate should demonstrate the ability to think critically and have an appetite for learning a broad range of chemistry techniques. Good communication and writing skills are essential.

Give the above, the candidate would be expected to use modern computational chemistry packages, including both ab initio and classical molecular dynamics programs, and hence experience in using these would be desirable but not essential as training will be provided. The experimental component will involve synthesis, and kinetic and thermodynamic measurements using NMR spectroscopy and spectrophotometry techniques. Again, experience in these techniques are desirable but less important than an understanding of these techniques.

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