Impact area: surface interactions

Partners: Manchester, Cambridge, Imperial and Illinois

The challenge: Fouling and deposits from carbon based (carbonaceous) materials such as asphaltenes, soot, cokes and scales reduce efficiency and reliability in engines, pipes and production process equipment by restricting or blocking flow. This can result in the cessation or poor performance of operations.

Images: Left shows a molecular model of idealised carbon-based deposit, based on Yen Mullins structures. Right shows carbonaceous deposits on a fuel injector.

Our objective: Modelling and characterising the interactions between these carbonaceous materials and surfaces will allow for a better understanding of fouling and deposition. This will lead to new strategies and inhibitor materials to prevent or mitigate these fouling processes.

The ICAM portfolio of ‘surface interaction’ projects are aimed at:

  • Understanding the origin and relationship of nucleation, aggregation, and deposition upon surfaces resulting in fouling and scaling.
  • Developing new additives to inhibit or resist fouling.
  • Strategies for predicting and management to minimise operations downtime.

Research solution: The research at ICAM will develop improved models of molecular structure and interactions which will enable a better mechanistic understanding of fouling and deposition. 

This will be underpinned by:

  • Synthesis, imaging and characterisation of surfaces and their interactions with synthetic ‘model’ and real carbonaceous materials.
  • Improved testing techniques for the development of new inhibitors.

Underpinning science - carbonaceous deposits:  The fundamentals of the ‘how’ (nucleation), ‘why’ (surface interactions) and ‘what’ (suspended aggregates) - from the molecular right up to the macro scale - that lead to deposition of these materials are poorly understood.

ICAM is working to understand the structures and morphologies of aggregates and deposits and the surface structures to which these adhere to.  By modelling and characterising these interactions a better understanding will lead to better inhibitor molecules and predictive tools.