TMCS is an EPSRC Centre for Doctoral Training operated by the Universities of Oxford, Bristol and Southampton.
In year one you will be based in Oxford with a cohort of around 12–15 other TMCS students, and will receive in-depth training in fundamental theory, software development, and chemical applications, delivered by academics from all three Universities. Successful completion of the year-one program leads to the award of an Oxford MSc, and progression to the 3-year PhD project based in Southampton, and detailed below.
Driving materials discovery using crystal structure prediction
One of the great challenges for computational chemistry is the prediction of solid state structure from a knowledge of chemical composition alone. The field of crystal structure prediction has made important advanced in recent years, particularly in the field of organic molecular crystals, where structure is determined by a subtle balance of weak intermolecular interactions. These methods are now becoming reliable for certain classes of molecules and current developments are broadening the types of molecules for which structure prediction is possible. One of the goals of crystal structure prediction is to use the predicted structures to anticipate materials properties, making the link from molecular structure to bulk properties. This is an essential step in the design and discovery of new materials with targeted properties. Our research group is actively developing crystal structure prediction methods, as well as the use of crystal structure prediction as the central method in computational approaches to discovering new materials.
In this project, which builds on the results of a recent 5-year European grant, we will explore the use of crystal structure prediction to drive a computational exploration of chemical space to search for molecules that lead to promising predicted materials properties. Areas of current interest are porous materials and organic electronics. The project will make use of force field and electronic structure based energy minimisation, energy landscape exploration and machine learning methods.