A review of methodologies to measure the bipolar charge distribution of nanoparticles is completed, including their advantages/disadvantages and sequential development. This summary also provides context for a new development, which uses an Aerodynamic Aerosol Classifier (AAC) and Differential Mobility Analyzer (DMA) in tandem for a similar purpose. It is demonstrated that the tandem AAC-DMA system overcomes some significant limitations of the previous methodologies, such as multiply-charged particle artefacts and low measurement signals. The tandem AAC-DMA methodology also has the sensitivity to detect other charging phenomena, such as the effects of different sample flow rates through the charger, free-ions downstream of the charger, the inlet insert on the 85Kr charger and different particle chargers (x-ray, old 85Kr and new 85Kr). The charge fractions of the particles at low-flow (0.6 L/min) through the new 85Kr charger agreed well (average absolute difference of 0.007) with widely-used charging theory. However, significant deviations from theory (up to a 0.044 difference in charge fractions) were found with a higher sample flow rate (1.2 L/min), with different exposure times to free-ions downstream of the charger, or with the inlet insert on the new 85Kr charger. It was found that regardless of flow rate, a soft x-ray charger resulted in charge fractions which deviated significantly from theory (up to a 0.084 difference in charge fractions), producing higher fractions of positively charged particles and lower fractions of negatively charged particles relative to theory. All of these deviations are likely due to the simplifying assumptions made by the charging theory. Therefore, rigorous measurement of particle charge distributions are necessary for accurate aerosol characterization, such as standard SMPS measurements.
Johnson, T. J., Nishida, R. T., Irwin, M., Symonds, J. P. R., Olfert, J. S., & Boies, A. M. (2020). Measuring the bipolar charge distribution of nanoparticles: Review of methodologies and development using the Aerodynamic Aerosol Classifier. Journal of Aerosol Science, 143. https://doi.org/10.1016/j.jaerosci.2020.105526