Optimizing Filtration Experiments for Length and Fractal Dimension Characterization of Non-Spherical Particles

By combination of a differential mobility analyzer (DMA) with a filter with uniform pores, namely a filter sensor, a new method for differentiating nanoparticles with various mass-mobility fractal dimensions, D_fm, was developed and validated experimentally and theoretically. The sensor is also able to measure the effective length (or maximum projected length) of nanoparticles with different shapes, which is an important parameter responsible for the lung deposition due to interception. At the same mobility diameter, it was observed that the compact NaCl had the highest penetration followed by partially sintered silver (Ag) aggregates and then the loose Ag and soot agglomerates. The result indicates that the stronger interception by the filter is correlated to the more elongated shape of the particles. A modified capillary tube model for predicting the penetration of Ag nanoparticles with different mass-mobility fractal dimensions was validated by experimental data. By using the validated model, this study found that the sensor could have a further enhanced sensitivity if the porosity and thickness of the filter were adjusted to 0.01 and 5m, respectively. The penetration differences obtained from the model are as high as 7-18%, 14-35%, and 24-40% between spheres and loose agglomerates (D_fm = 2.1) for 50-100, 100-300, and 300-1000 nm particles as the filter pore sizes are 0.4, 1, and 3m, respectively. This new filter sensor can measure the effective length and mass-mobility fractal dimension in nearly real-time and may be applied in nanotoxicity studies and quality control of nanomaterial productions (e.g., by flame reactors).