Nanoparticle penetration efficiency prediction model in conductive and non-conductive coils for aerosol measurement system: Experimental research and critical review

Abstract

Nanoparticles play an important role across industries such as drug delivery, energy storage systems, semiconductor manufacturing, and environmental research. However, the utilization of nanoparticles is often hindered by particle loss during transfer. In this study, we developed a predictive model for the penetration efficiency of aerosol in the three-turn coil with conductive (Copper and Tygon) and non-conductive (Teflon) materials. We conducted samplings for NaCl particles under controlled conditions and atmospheric aerosol particles directly from the ambient environment. The results demonstrated that penetration efficiency strongly depends on coil material, with non-conductive Teflon exhibiting significant particle losses due to electrostatic effects. Comparative analysis with existing models revealed their limitations in capturing the coupled influence of diffusion, secondary flow, and electrostatic effects in multi-turn coil configurations. To overcome this limitation, we developed a novel predictive model incorporating a new parameter (Γ), which enables accurate estimation of nanoparticle penetration efficiency in multi-turn coils under the broadest operating conditions. By accounting for electrostatic forces, our model is applicable to both conductive and non-conductive coil types, achieving the highest accuracy, with average errors of 9.37% for conductive and 5.97% for non-conductive coils. This study also provides practical design guidelines and online tool for improving aerosol-based systems.