Modeling pressure drop values across ultra-thin nanofiber filters with various ranges of filtration parameters under an aerodynamic slip effect.

Computational fluid dynamics simulations of fibrous filters with 56 combinations of different fiber sizes, packing densities, face velocities, and thicknesses were conducted for developing models that predict pressure drops across nanofiber filters. The accuracy of the simulation method was confirmed by comparing the numerical pressure drops to the experimental data obtained for polyacrylonitrile electrospun nanofiber filters. In the simulations, an aerodynamic slip effect around the surface of the small nanofibers was considered. The results showed that, unlike in the case of conventional filtration theory, pressure drops across the thin layers of electrospun nanofiber filters are not proportional to the thickness. This might be a critical factor for obtaining precise pressure drops across the electrospun nanofiber filters with extremely thin layers. Finally, we derived the product of drag coefficient and Reynolds number as a function of packing density, Knudsen number, and ratio of thickness to fiber diameter to get the correlation equation for pressure drop prediction. The obtained equation predicted the pressure drops across the nanofiber filters with the maximum relative difference of less than 15%.

Accurate measurements of particle emissions from a three-dimensional printer using a chamber test with a mixer-installed sampling system.

Recently, three-dimensional (3D) printing has attracted attention as a new manufacturing technology. However, there is lack of data and regulations regarding the emissions of ultrafine particles from 3D printers. Therefore, we investigated particle emissions from a 3D printer using a chamber system. The test system was improved by installing a developed mixer for accurate measurement. Without a mixer, the particle concentration was unstable depending on the sampling point; however, reliable data with good uniformity were obtained by installing a mixer. Using the test system with a mixer, we investigated particle emissions from a 3D printer during operation. Filaments made each of acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) were used as the printing material. The effects of nozzle temperature and printing time were investigated. Compared to the effect of the printing time, the nozzle temperature had greater impact on the particle emissions. The dominant particle size for the emissions from a 3D printer is less than 10 nm, and the particle concentration decreased with increasing particle size.

Detection of Airborne Nanoparticles through Enhanced Light Scattering Images.

A new method is proposed in this paper to detect airborne nanoparticles, detecting the light scattering caused by both the particle and the surrounding molecules, which can surpass the limitations of conventional laser optical methods while maintaining simplicity and cost-effectiveness. This method is derived from a mathematical analysis that describes the particle light scattering phenomenon more exactly by including the influence of light scattered from surrounding gas molecules. The analysis shows that it is often too much of a simplification to consider only light scattering from the detected nanoparticle, because light scattering from the surrounding gas molecules, whether visible or invisible to the sensor, is important for nanoparticle detection. An image detection approach utilizing the light scattering from surrounding air molecules is described for the detection of airborne nanoparticles. Tests using monodisperse nanoparticles confirm that airborne particles of around 50 nm in size can even be detected using a low-cost testing device. This shows further that even when using a simple image processing code, captured particle light scattering images can be converted digitally into instantaneous particle counts or concentrations. The factors limiting conventional pulse detection are further discussed. This new method utilizes a simple static light scattering (SLS) approach to enable the development of new devices with better detection capabilities, paving the way for the further development of nanoparticle detection technology.

Quantitative analysis of droplet deposition produced by an electrostatic sprayer on a classroom table by using fluorescent tracer.

Due to the ongoing COVID-19 pandemic situation, measures to mitigate the risk of transmission of the SARS-CoV-2 virus in an indoor setting are urgently needed. Among the various types of disinfectant methods, electrostatic spraying is often applied to decontamination in public places. For quantitatively characterizing electrostatic spraying, we developed the novel evaluation method by using a fluorescent tracer. By applying this method, we performed three different experiment cases (static test on a table, static test on a cylinder, and dynamic test on a table) to figure out its unique characteristics (Coulombic fission and wraparound effect) and measure its performance in various aspects. To be specific, bimodal distribution with peak sizes of ~10 and ~100 µm was found due to Coulombic fission. Otherwise, a unimodal distribution with a peak size of ~100 µm occurred for the uncharged droplets. As a result, the effective contact area increased by 40-80 % due to small progeny droplets. The wraparound effect was examined on two different cylinders: copper (Cu) and polyvinyl chloride (PVC) pipe. When the target surface was not charged (Cu 0 kV and PVC 0 kV), the average normalized concentrations on the backside of the cylinder (θ = 180°) increased by around 67 % for charged droplets. Meanwhile, when the target surface was highly charged (PVC -19 kV), the average normalized concentrations at θ = 180° were increased more than two times for charged droplets.