Healable Polymer Materials

The past four decades of science have witnessed how chemists have learnt from nature, in part by trial and error as well as elegant design, to understand and master the use of weak non-covalent interactions and self-assembly processes in synthetic systems to realise complex multi-component assemblies that exhibit attractive functionalities. The incorporation of molecular recognition units within polymers has afforded a new class of materials – supramolecular polymers – that, on account of weak reversible non-covalent interactions within their assemblies, are dynamic in nature. The Hayes group have discovered several supramolecular polymer systems that are healable in nature[1-4] – when damaged their physical properties can be recovered by application of an appropriate stimulus such as heat or light. Notably. supramolecular polyurethanes have been generated that heal at body temperature[5] – such materials offer great potential in the treatment of wounds or burns. This project targets the discovery of healable supramolecular polymer networks for use in biomedical devices. The project will provide excellent training in the field of polymeric materials – it will involve organic and polymer synthesis, characterisation of the new materials (using techniques such as NMR, IR, UV spectroscopy, mass spectrometry and thermal analysis (DSC, TGA) in the University’s Chemical Analysis Facility) plus GPC analysis (available in the Hayes group research laboratory) and physical assessment of the polymeric materials via rheology and tensiometry (these instruments are available in the Hayes research laboratory). In addition to gaining invaluable scientific technical skills, this project will also develop the ability of the postgraduate student to conduct independent research by providing training on the use of databases (such as Web of Knowledge, Scifinder Scholar, Reaxys), presentation skills and writing reports. By the end of the PhD training, the student will be able to design and execute reactions, interpret complex analytical datasets, and summarise this information in a variety of formats (such as in presentations at group meetings or international conferences or in peer-reviewed publications).