Controlling how materials form and deposit at the nanoscale is a central challenge in modern chemical manufacturing. This project will explore how trace contaminants influence the growth and fouling behaviour of sodium silicate, an industrially important material, under realistic processing conditions. Despite its widespread use, the link between particle formation in solution and surface deposition remains poorly understood, particularly in continuous-flow systems, limiting our ability to control product quality and process efficiency.

You will investigate how contaminants affect both silicate growth and surface interactions using advanced fluorescence imaging within controlled flow environments. By tracking silicate species in real time, the project will establish direct links between solution-phase dynamics and fouling at interfaces. These experiments will be complemented by AI-assisted image analysis and molecular dynamics (MD) simulations, providing both quantitative and atomistic insight into the underlying mechanisms.

The project will deliver fundamental understanding of colloidal growth, aggregation, and surface interactions in complex systems, knowledge that is broadly relevant to materials synthesis, soft matter science, and chemical processing.

This multidisciplinary project spans advanced imaging, physical chemistry, and computational modelling, and will equip the student with skills in fluorescence microscopy, experimental design, AI-driven data analysis, and MD simulation. These capabilities are highly valued in both academic and industrial research and development. The project will include industrial engagement with partners in the silica and materials sector.