Efficient 3D Printing of N95 Face Mask Filters

N95 masks have been in much demand during the COVID-19 pandemic, due to being breathable and highly effective at protecting the public, while also reducing environmental waste by being reusable. 3D printed N95 mask filters are also antimicrobial or sterilizable and suitable for flexible design. However, these filters have a slow production rate, something that is being tackled through a workflow involving binder-jet 3D printing, micro-CT scanning, 3D image processing, and computational fluid dynamic (CFD) simulation. Researchers at the University of Pittsburgh, ExOne, Ansys, and Synopsys have worked on developing an efficient digital prototyping process to save time and resources when manufacturing 3D-printed copper and stainless-steel mask filters.

Optimizing 3D Printed Filters

Different approaches came together to create the filter workflow:

• Different filter samples were created by ExOne using binder-jet printing and sintering, and experimental data acquired.
• The samples were scanned on a Bruker SkyScan 12972 uCT machine.
• Ansys Simpleware software was used to import image data for segmentation of the porous structure, and for generation of simulation-ready CFD meshes
• Ansys Fluent software was used to analyze the behavior of N95 masks in normal operation, including porous resistance, with simulations run on Simpleware software meshes refined for different conditions to predict which metal powder/sintering combinations met acceptable filtration standards.
• Results showed improved filtration efficiency for 5 µm particles against 1 µm particles, and how studying high and low flow regions helps provide insights into mask design to improve performance.

Future Impact

Given the continued demand for N95 face masks and efficient manufacturing of filters, this combination of binder-jet 3D printing and iterative optimization of printing and post-processing parameters shows promise for increasing the reusability of sterilizable metal N95 filters. In addition, design optimization through digital prototyping only takes about four days on average, compared to approximately 21 days with physical methods, and also reduces material waste.

We were excited to take part in this project, especially given the ways this method can be adapted to study other characteristics and improve our understanding of pore behavior, with the benefit of mitigating against large-scale disposal of single-use PPE.

Learn more about Ansys Simpleware software.