3D-Printed Microfiltration Membranes via Dual-Wavelength Microstereolithography
Hanieh Bazyar (TU Delft - ChemE/Transport Phenomena)
Shang Che Wu (Student TU Delft)
Irem Gurbuz (TU Delft - Engineering Thermodynamics)
Wesley van Vliet (Photosynthetic B.V.)
Alexander Kostenko (Photosynthetic B.V.)
Jimmy G. Jean (TU Delft - Group Çaglar)
Guillaume Broggi (TU Delft - Group Çaglar)
B. Caglar (TU Delft - Group Çaglar)
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Abstract
A new and sustainable membrane manufacturing method is 3D printing, which reduces the number of fabrication steps, waste production, and the corresponding CO2emissions. It further enables fabricating membranes with well-defined pore size, shape, and configuration. Here, we study 3D printing of microfiltration membranes using a novel dual-wavelength microstereolithography method. Via the gradient descent method, we are able to calculate and control a printable membrane with micrometer precision, enabling the possibility of printing membranes directly. Hydrophilic porous membranes with cylindrical microscale pores (≈10 μm in diameter) are printed from polyethylene glycol diacrylate (PEGDA). Membrane printing procedure and postprocessing steps are thoroughly investigated to print consistent membranes with uniform thickness. The membranes are fully characterized using SEM, FTIR, contact angle, and surface roughness measurements. The pure water permeability and separation performance of the 3D-printed membrane are further investigated and compared with those of commercial hydrophilic PTFE membranes. The 3D-printed membranes show similar permeability values to those of commercial membranes and could successfully separate oil droplets from oil-in-water emulsions. The membranes’ permeability is further predicted using a 1D tube model and numerical modeling. The effect of material’s property (e.g., swelling) and pore deformation during pressurization are studied to understand the discrepancy between the calculated and the experimental permeability values. The results provide valuable insights into the permeability prediction of 3D-printed membranes and the corresponding design optimization.