In order to provide the population with consistent and science-based advice on preferred materials for face masks, we are characterizing the microstructure of different materials using X-ray microfocus computed tomography (microCT), and we use these datasets to simulate the pressure drop (i.e. measure for breathability). We validate our measurements with physically measured filter efficiency and pressure drop, and in this way, we try to develop a “virtual testing platform” for the characterization of the filter efficiency and pressure drop of potential filter and mask materials.
We characterize the morphological parameters of different filter materials and textile masks from our high-resolution microCT datasets. Using these datasets, we additionally simulate the pressure drop through the material (using AVIZO – ThermoFisher).
We see a strong correlation between our simulated pressure drop values and the physically measured pressure drop (performed by VITO, Mol, Belgium, in agreement with the NBN guidelines).
Additionally, we are using statistical modelling (Partial Least Squared Regression – in close collaboration with Prof. Lies Geris (ULiège and KU Leuven)) to try to predict, based on our micro-CT based measurements, the filter efficiency. Preliminary analysis shows that we can predict the filter efficiency for particles down to 3µm with up to 82.4%. Although improvements are still being made, we are getting close to a virtual testing platform for materials for potential face masks!