Impact of Particle Shape and Surface Group on Membrane Fouling.

Membrane fouling remains one of the most critical drawbacks in membrane filtration processes. Although the effect of various operating parameters-such as flow velocity, concentration, and foulant size-are well-studied, the impact of particle shape is not well understood. To bridge this gap, this study investigated the effect of polystyrene particle sphericity (sphere, peanut and pear) on external membrane fouling, along with the effect of particle charge (unmodified, carboxylated, and aminated).

Transient Prediction of Nanoparticle-Laden Droplet Drying Patterns through Dynamic Mode Decomposition.

Nanoparticle-laden sessile droplet drying has a wide impact on applications. However, the complexity affected by the droplet evaporation dynamics and particle self-assembly behavior leads to challenges in the accurate prediction of the drying patterns. We initiate a data-driven machine learning algorithm by using a single data collection point via a top-view camera to predict the transient drying patterns of aluminum oxide (AlO) nanoparticle-laden sessile droplets with three cases according to particle sizes of 5 and 40 nm and AlO concentrations of 0.