Nanoparticle agglomerates are pervasive in atmospheric sciences, air pollution, and manufacturing of powdered materials, yet studies for filtration of nanoparticle agglomerates are still scarce compared to those for spherical particles. We investigated loading of soot nanoparticle agglomerates on fibrous air filter media. The soot agglomerates were generated from a diffusion burner with propane gas as fuel and compressed air as oxidant/sheath. The mode of the number distribution was determined to be 120 nm. A Differential Mobility Analyzer (DMA)—Aerosol Particle Mass Analyzer (APM) system was used to measure the mass of agglomerates as a function of the mobility size, which gave a mass-mobility exponent of 1.9 ± 0.1. Using transmission electron microscopy (TEM), we found that the primary particles in the agglomerates had a mean diameter of 28 nm with a geometric standard deviation of 1.26. Loading experiments were carried out with the face velocity of 10 cm/s on a fiberglass filter media. The pressure drop increased approximately linearly with the loading mass. The porosity of the cakes was calculated using cake mass and cake thickness, and the average cake porosity was 0.95. We found that the model of Endo et al. (1998) for cake loading was applicable to soot agglomerate loading. The cake could be regarded as formed by primary particles in soot agglomerates, and agglomerates are indistinguishable once deposited in the cake. When the size distribution of the primary particles was used in the model of Endo et al. good agreement between the experimental and computed results was obtained.
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The authors thank the support of members of the Center for Filtration Research: 3M Corporation, Boeing Company, Cummins Filtration Inc., Donaldson Company, Inc., E. I. du Pont de Nemours and Company, Entegris Inc, Samsung Semiconductor Inc., Shigematsu Works CO., LTD, TSI Inc., and W. L. Gore & Associates and the affiliate member National Institute for Occupational Safety and Health (NIOSH). Parts of this work were carried out in the University of Minnesota I.T. Characterization Facility, which receives partial support from NSF through the NNIN program. Also, Jacob H. Scheckman acknowledges support from National Science Foundation Grant BES-0646507.