Development of Electrospun Polyacrylonitrile Aerosol Filter Media for Respiratory Personal Protective Equipment

被引:1
作者
Ewell, Nathan [1 ]
Lee, Jeonyoon [1 ]
Mulherin, Kristen [2 ]
Rutledge, Gregory C. [1 ]
机构
[1] MIT, Dept Chem Engn, Cambridge, MA 02139 USA
[2] Adv Funct Fabr Amer, Cambridge, MA 02139 USA
来源
ACS APPLIED ENGINEERING MATERIALS | 2024年 / 2卷 / 04期
关键词
nanofiber; electrospinning; filter; aerosol; respirator; PPE; face mask; polyacrylonitrile; NANOPARTICLE FILTRATION; NANOFIBERS; FORCES;
D O I
10.1021/acsaenm.4c00083
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The COVID-19 pandemic highlighted the importance of respiratory personal protective equipment (PPE) as a means of reducing the spread of disease via aerosolized droplets. For years, N95-type filtering facepiece respirators based on meltblown polypropylene nonwovens have been the technology of choice for healthcare professionals and personal use. However, their reliance on electrostatic charges to achieve an acceptable trade-off between filtration efficiency and pressure drop has led to concerns about shelf life, reusability, quality control, and versatility of materials. In this study, we show that media in which an electrospun polyacrylonitrile (PAN) nonwoven serves as the active layer, comprising fibers of much smaller diameter than typical meltblown fibers, can achieve high levels of filtration efficiency combined with low pressure drop without the assistance of electrostatic charging. Moreover, the aerosol filtration data is well-described by the slip flow-modified Kuwabara model for pressure drop and a single fiber efficiency model that takes into account particle collection via diffusion, interception, and impaction. These models may be used to guide the further design of nanofiber filters. Combined with a spunbond substrate, the proposed filtration media resolves practical concerns regarding mechanical robustness and residual solvent, and it has been fabricated into filtering facepiece respirators that meet N95 filtration standards when tested by standard methods.
引用
收藏
页码:1082 / 1093
页数:12
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