Plastic fragmentation in the oceans and in museums

Project ID: 2228cd1242 (You will need this ID for your application)

UCL Lead department: Bartlett School of Environment, Energy and Resources

Project Summary:

This project is an opportunity to engage with two important and challenging problems facing society. The persistence of plastic waste in the natural environment is one of the big challenges facing humanity. In contrast, plastic museum artefacts are known for their fragility and impermanence, a problem that risks the loss of unique modern cultural heritage. Common to both problems is a need to understand the way in which plastics degrade over time. Environmental factors such as light, heat or moisture will cause chemical degradation in plastics, changing properties such as polymer molecular weight or chemical structure. This is followed by fragmentation of the object into smaller pieces. Previous work by the primary supervisor has developed mathematical models that predict the rates of chemical degradation processes. However, rates of fragmentation are currently unknown. This means that we don’t know how long plastic waste objects persist in different environments, how quickly they fragment into microplastic pollution or fully understand the fragility of plastics in museums. This project will address these gaps, exploring (i) relationships between chemical degradation and fragmentation, (ii) whether thresholds of chemical change can be identified beyond which fragmentation is more likely, and (iii) how this knowledge can be incorporated into existing models to predict fragmentation rates. In this project you will work with an interdisciplinary team, covering polymer degradation, heritage, marine and material science. You will use analytical techniques such as GPC, GC/MS and FTIR and NMR spectroscopies to measure the properties of plastics. You will design and implement experiments that simulate the physical stresses experienced by plastic objects in both the natural environment and in museums. Data from these experiments will be used in existing mathematical models.
We are looking for a motivated candidate with a background in chemistry, engineering or material science.