Machine learning modeling of polycarbonate ultrafiltration membranes at different temperatures, AlO nanoparticle volumes, and water ratios.

The efficacy of novel polycarbonate ultrafiltration, aluminum oxide nanoparticle (AlO-NPs) volume fraction, temperature, and water/ethylene glycol (EG) ratio were evaluated to determine the thermophysical properties of the membrane. 5%-10% of AlO-NPs have been added to the PC. A machine learning approach was used to compare the volume fraction of AlO-NPs, the temperature, and the water-to-ethylene glycol (EG) ratio.