Using Computational Fluid Dynamics to Model Antibacterial Surface Textures (PANTERJ_U26EMP)

The growth and proliferation of bacterial communities in biofilms on surfaces is a leading cause of hospital-acquired infections [1]. This is problematic on devices that cannot be readily or regularly sterilised, such as medical implants, and is particularly serious when biofilms form of antibiotic-resistant bacteria. It is therefore desirable to create surface coatings that prevent the attachment and/or proliferating of bacteria.

One promising technique is to physically structure the surface – creating a microscopic surface texture. Nanoscale textures have the capacity to disrupt the cell membranes and so kill bacteria on contact. A less explored yet promising route however is to use much larger surface features (microns to millimetres in size).

These surfaces have been observed to show reduced biofilm formation compared to smooth (unstructured) surfaces, when bacterial suspensions are flowed across them. However, the microscale features are far too large in scale to kill bacteria on contact. It has instead been hypothesised that the surface structures are influencing the fluid flow to prevent bacterial adhesion, possibly through the action of effectively mixing and diluting chemical signals that indicate the presence of a critical mass of bacteria to form a biofilm.

Towards testing this hypothesis, this project will examine how micro- and milli-scale surface roughness influences fluid flow over a surface, with particular emphasis on how the roughness influences mixing of a