A novel fully automatic design approach of a 3D printed face specific mask: Proof of concept

Masks and respirators for prevention of respiratory infections: a state of the science review

SUMMARYThis narrative review and meta-analysis summarizes a broad evidence base on the benefits-and also the practicalities, disbenefits, harms and personal, sociocultural and environmental impacts-of masks and masking. Our synthesis of evidence from over 100 published reviews and selected primary studies, including re-analyzing contested meta-analyses of key clinical trials, produced seven key findings. First, there is strong and consistent evidence for airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory pathogens. Second, masks are, if correctly and consistently worn, effective in reducing transmission of respiratory diseases and show a dose-response effect. Third, respirators are significantly more effective than medical or cloth masks. Fourth, mask mandates are, overall, effective in reducing community transmission of respiratory pathogens. Fifth, masks are important sociocultural symbols; non-adherence to masking is sometimes linked to political and ideological beliefs and to widely circulated mis- or disinformation. Sixth, while there is much evidence that masks are not generally harmful to the general population, masking may be relatively contraindicated in individuals with certain medical conditions, who may require exemption. Furthermore, certain groups (notably D/deaf people) are disadvantaged when others are masked. Finally, there are risks to the environment from single-use masks and respirators. We propose an agenda for future research, including improved characterization of the situations in which masking should be recommended or mandated; attention to comfort and acceptability; generalized and disability-focused communication support in settings where masks are worn; and development and testing of novel materials and designs for improved filtration, breathability, and environmental impact.

In Silico Fit Evaluation of Additively Manufactured Face Coverings

In response to the respiratory protection device shortage during the COVID-19 pandemic, the additive manufacturing (AM) community designed and disseminated numerous AM face masks. Questions regarding the effectiveness of AM masks arose because these masks were often designed with limited (if any) functional performance evaluation. In this study, we present a fit evaluation methodology in which AM face masks are virtually donned on a standard digital headform using finite element-based numerical simulations. We then extract contour plots to visualize the contact patches and gaps and quantify the leakage surface area for each mask frame. We also use the methodology to evaluate the effects of adding a foam gasket and variable face mask sizing, and finally propose a series of best practices. Herein, the methodology is focused only on characterizing the fit of AM mask frames and does not considering filter material or overall performance. We found that AM face masks may provide a sufficiently good fit if the sizing is appropriate and if a sealing gasket material is present to fill the gaps between the mask and face. Without these precautions, the rigid nature of AM materials combined with the wide variation in facial morphology likely results in large gaps and insufficient adaptability to varying user conditions which may render the AM face masks ineffective.

A framework for effective face-mask contact modeling based on finite element analysis for custom design of a facial mask

A novel contact model is presented to efficiently solve a face-mask contact problem by using the finite element (FE) method for the optimized design of a custom facial mask. Simulation of contact pressure for various mask designs considering material properties of the face allows virtual evaluation of the suitability of a mask design for a person’s face without conducting empirical measurement of the face-mask contact pressure. The proposed contact model is accomplished by combining three approaches to reduce the calculation cost of simulating the face-mask contact: (1) use of a simplified and modifiable mask model that applies a spline curve to design points; (2) reduction of the FE model of the face by applying static condensation; and (3) application of a contact assumption that uses the Lagrange multiplier method. A numerical case study of a medical mask design showed that the proposed model could calculate the face-mask contact pressure efficiently (0.0448 sec per design). In a pilot usability experiment, the measured contact pressure was found similar values (range of mean contact pressure: 0.0093 ~ 0.0150 MPa) to the estimated values (range of mean contact pressure: 0.0097 ~ 0.0116 MPa).

Masks for COVID-19

Sustainable solutions on fabricating and using a face mask to block the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread during this coronavirus pandemic of 2019 (COVID-19) are required as society is directed by the World Health Organization (WHO) toward wearing it, resulting in an increasingly huge demand with over 4 000 000 000 masks used per day globally. Herein, various new mask technologies and advanced materials are reviewed to deal with critical shortages, cross-infection, and secondary transmission risk of masks. A number of countries have used cloth masks and 3D-printed masks as substitutes, whose filtration efficiencies can be improved by using nanofibers or mixing other polymers into them. Since 2020, researchers continue to improve the performance of masks by adding various functionalities, for example using metal nanoparticles and herbal extracts to inactivate pathogens, using graphene to make masks photothermal and superhydrophobic, and using triboelectric nanogenerator (TENG) to prolong mask lifetime. The recent advances in material technology have led to the development of antimicrobial coatings, which are introduced in this review. When incorporated into masks, these advanced materials and technologies can aid in the prevention of secondary transmission of the virus.

A feasible route for the design and manufacture of customised respiratory protection through digital facial capture

The World Health Organisation has called for a 40% increase in personal protective equipment manufacturing worldwide, recognising that frontline workers need effective protection during the COVID-19 pandemic. Current devices suffer from high fit-failure rates leaving significant proportions of users exposed to risk of viral infection. Driven by non-contact, portable, and widely available 3D scanning technologies, a workflow is presented whereby a user’s face is rapidly categorised using relevant facial parameters. Device design is then directed down either a semi-customised or fully-customised route. Semi-customised designs use the extracted eye-to-chin distance to categorise users in to pre-determined size brackets established via a cohort of 200 participants encompassing 87.5% of the cohort. The user’s nasal profile is approximated to a Gaussian curve to further refine the selection in to one of three subsets. Flexible silicone provides the facial interface accommodating minor mismatches between true nasal profile and the approximation, maintaining a good seal in this challenging region. Critically, users with outlying facial parameters are flagged for the fully-customised route whereby the silicone interface is mapped to 3D scan data. These two approaches allow for large scale manufacture of a limited number of design variations, currently nine through the semi-customised approach, whilst ensuring effective device fit. Furthermore, labour-intensive fully-customised designs are targeted as those users who will most greatly benefit. By encompassing both approaches, the presented workflow balances manufacturing scale-up feasibility with the diverse range of users to provide well-fitting devices as widely as possible. Novel flow visualisation on a model face is presented alongside qualitative fit-testing of prototype devices to support the workflow methodology.

Characterization of performance and disinfection resilience of nonwoven filter materials for use in 3D-printed N95 respirators

The COVID-19 pandemic has caused a high demand for respiratory protection among health care workers in hospitals, especially surgical N95 filtering facepiece respirators (FFRs). To aid in alleviating that demand, a survey of commercially available filter media was conducted to determine whether any could serve as a substitute for an N95 FFR while held in a 3D-printed mask (Stopgap Surgical Face Mask from the NIH 3D Print Exchange). Fourteen filter media types and eight combinations were evaluated for filtration efficiency, breathing resistance (pressure drop), and liquid penetration. Additional testing was conducted to evaluate two filter media disinfection methods in the event that the filters were reused in a hospital setting. Efficiency testing was conducted in accordance with the procedures established for approving an N95 FFR. One apparatus used a filter-holding device and another apparatus employed a manikin head to which the 3D-printed mask could be sealed. The filter media and combinations exhibited collection efficiencies varied between 3.9% and 98.8% when tested with a face velocity comparable to that of a standard N95 FFR at the 85 L min-1 used in the approval procedure. Breathing resistance varied between 10.8 to >637 Pa (1.1 to > 65 mm H2O). When applied to the 3D-printed mask efficiency decreased by an average of 13% and breathing resistance increased 4-fold as a result of the smaller surface area of the filter media when held in that mask compared to that of an N95 FFR. Disinfection by dry heat, even after 25 cycles, did not significantly affect filter efficiency and reduced viral infectivity by > 99.9%. However, 10 cycles of 59% vaporized H2O2 significantly (p < 0.001) reduced filter efficiency of the media tested. Several commercially available filter media were found to be potential replacements for the media used to construct the typical cup-like N95 FFR. However, their use in the 3D-printed mask demonstrated reduced efficiency and increased breathing resistance at 85 L min-1.