Aerosol

(1) Aerosol measurement and characterization

1-2) Developing penetration efficiency prediction model for aerosol in the coiled system.

Reference: Seungjae Gwak (First author), Chungsup Kim, Yusun Lee, Dong-Bin Kwak, "Nanoparticle penetration efficiency prediction model in conductive and non-conductive coils for aerosol measurement system: Experimental research and critical review", Advanced Powder Technology, Volume 36, Issue 10, 2025, 105027, ISSN 0921-8831, https://doi.org/10.1016/j.apt.2025.105027.

■ Background (Why important?)

• To enhance the efficiency of nanotechnology, it is essential to precisely quantify particle loss occurring within the system. When nano-sized particles pass through a system (channel), Brownian diffusion becomes the dominant mechanism driving particle loss due to their extremely small size. Furthermore, when the channel is bent, the fluid experiences centrifugal force toward the center of the curvature, resulting in radial and tangential velocities, as well as secondary flow. This can result in further particle losses because the particles are taken from the center of the channel cross-sectional area toward the wall. In cases where the coil is made of non-conductive material (e.g., Teflon), electrostatic force may further increase particle loss (Figure a). However, existing penetration efficiency prediction models ("Gormley and Kennedy", "Yook and Pui", and "Lin et al.") have limitations on capturing these combined mechanisms.

■ Resluts (My contributions)

• Figure b: Experimental setup to measure the coil penetration efficiency under controlled conditions. / Figure c: Developed a predictive model for nanoparticle losses in conductive and nonconductive multi-turn coil systems, applicable to laminar flow regimes, considering Brownian diffusion, secondary flow induced by the coiled configuration, and electrostatic losses due to charge attraction in nonconductive materials. Our model not only achieves the higest accuracy than existing models, but is also applicable in more complex conditions where conventional models often fail. 

• Through Pearson correlation matrix (Sensitivity analysis; Figure d) and Multi-variable interaction studies (Simulation using our model; Figure e), we systematically investigated the relative contributions of Brownian diffusion, secondary flow, and electrostatic effects  in nanoparticle loss and penetration efficiency within coiled systems. Electrostatic forces were found to dominate particle losses, diffusion played a secondary role, and secondary flow contributed only marginally. Also, coil length, particle size, and flow rate strongly affect loss behavior, whereas the coil curvature ratio has negligible impact.

• Finally, provided practical design guideline for aerosol measurement system and developed a user-friendly engineering web design tool. Figure f and Figure g shows flow chart and image of this web design tool.

[Three core functions]

    (i) Penetration Efficiency Calculation based on our empirical model.

    (ii) Inverse Design for Coil System Configuration – determines optimal coil length and curvature ratio.

    (iii) ​Inverse Design for System Operational Conditions - identifies optimal flow rate  and particle diameter for a given coil geometry.

    (Web Design Tool URL: https://sites.google.com/g.seoultech.ac.kr/nel/design-tool/coil-penetration)

(1) Aerosol measurement and characterization

1-1) Characterization of particle size distribution for semiconductor CMP slurry.

Reference: Seongmin Cho, Yongjae Cho, Yusun Lee, Seungjae Gwak (Co-author), Heedo Seo, Su Bin Min, Young June Won, Min-Cheol Cho, Jung-Hun Noh, Dong-Bin Kwak, "Liquid Particle Monitoring System Utilizing Aerosol Metrology and Data Processing Algorithm: CMP Slurry Application", Measurement, https://doi.org/10.1016/j.measurement.2025.119624

Reference: Seongmin Cho, Yongjae Cho, Alexa Roux, Seungjae Gwak (Co-author), Daniel R. Troolin, Hyeon Gi Lee, Dong-Bin Kwak, "Nano-Liquid Particle Monitoring System for Colloidal Nanoparticle Characterization with Optimized Aerosol Generation: Virtual Impactor and Large Droplet Removal for Non-Volatile Residue Minimization", Measurement Science and Technology (Under Review)

■ Background (Why important?)

• Precise control and measure of particle size distribution in Chemical Mechanical Polishing (CMP) slurry is critical, as large or agglomerated particles can cause wafer defects in semiconductor manufacturing (Figure a). While Dynamic Light Scattering (DLS) and Particle Tracking Analysis (PTA)  are commonly used for liquid-phase analysis, DLS struggles with multimodal distributions and repeatability, and PTA is limited by optical sensitivity and screening effect from larger particles. Scanning Electron Microscopy (SEM) offers detailed morphology at high resolution, but its complex sample preparation, high cost, and need for skilled operation make it unsuitable for routine industrial use. Finally, Electro-spay (ES) provied superior resolution, but it requires significant expertise and precise tuning, making it less accessible for routine industrial applications.

■ Resluts (My contributions)

• Assisted in characterization of particle size distribution for semiconductor CMP slurry (Hydrosol to Aerosol measurement): Supported experiments and results analysis. To ensure reliability and repeatability, we converted the hydrosol-state polystyrene latex nanospheres (PSLs) and two types of CMP slurries (silica and ceria)  into aerosols, and measured their particle size distributions using Atomizer or Nano-LPMGen integrated Scanning Mobility Particle Sizer (SMPS) (Figure b). This nano-liquid particle monitoring system, based on optimized aerosol generation and detection, enabled consistent and accurate characterization of nanoscale colloidal abrasives (Figure c).

(2) Environmental and Public health application

2-2) Bio-aerosol behavior: Quantifying airborne viral RNA copies over time.

Reference: Seungjae Gwak (First author), Seongmin Cho, David Y.H. Pui, Dong-Bin Kwak, "Mathematical Modeling of Viral RNA Copies in Indoor Environments: Pre-processor for Risk Assessment and Decision-Making Support Tool for Public Health", Risk Analysis (Under Review)

■ Background (Why important?)

• When respiratory patients speak, cough, or sneeze, they release saliva droplets containing viral RNA into the air (Figure a). These bio-aerosols do not fully evaporate due to the presence of non-volatile components such as viral RNA, and are affected by gravity, eventually settling onto the ground. As a result, according to the World Health Organization (WHO), due to reduction mechanisms such as viral half-life, ventilation/filtration, and gravitational settling (Figure b), the total number of viral RNA copies changes over time. However, current viral RNA detection technologies (i.e., RT-qPCR or Air-sampling) have limitations in quantitatively assessing airborne viral RNA of expelled saliva droplets in real time. Moreover, existing quanta-based infection risk assessment models have not accurately handle saliva droplet airborne lifetime leading to simplified calculation process.

■ Resluts (My contributions)

• Developed simulation-based (mathematical) framework to quantitatively predict airborne viral RNA copies over time by incorporating key physical and biological parameters, including particle volume contribution with mass uncertainty (Figure c), viral half-life, viral load, saliva droplet airborne lifetime applicable over diverse environmental conditions (Figure d: resolving saliva droplet evaporation), exhalation mechanisms, and ventilation effects. Aside from that, due to its modular and physics-based structure, our model is broadly applicable to various respiratory viruses.

• The results show that viral half-life has little effect on airborne RNA copies in typical indoor environments excluding extreme disinfection conditions such as deliberate UV-C irradiation or acidification protocols, whereas airborne lifetime governed by droplet size and settling dominates viral persistence (Figure e). Using viral load data from multiple viruses, we further classified patient groups into asymptomatic, mild, and severe cases to perform stratified trend analysis, enabling more accurate and representative comparisons across infection severities and indoor conditions (Figure f).

• Validation of our model using experimental data from previous studies demonstrated a high level of accuracy (Figure g). Based on these results, we developed online web tool (NEL.RNA.Copies.calc) implementing our model (Figure h). This tool enables customization that reflects the large variations observed across individuals and allows users to directly adjust inputs and immediately analyze scenario-specific outcomes. Therefore, our model can serve as (1) pre-processor that supplies immediately usable, time resolved inputs for infection-risk assessment modeling studies and (2) decision-making support tool that enables rapid exploration of environments, behaviors, and control strategies, facilitating public-health intervention.

    (Web Tool URL: https://sites.google.com/g.seoultech.ac.kr/nel/design-tool/indoor-rna-copies)

(2) Environmental and Public health application

2-1) Developing cigarette sampling system and deriving dosing algorithm per single puff.

Reference: Seungjae Gwak† (Co-First author), Chungsup Kim†, Hyeongkyu Kwon, Jonghyun Lee, Yongjae Cho, Seongmin Cho, Yusun Lee, Dong-Bin Kwak, "Comparison of Particle Size Distributions between Conventional Cigarettes and Electronic Cigarettes based on Aerosolization Mechanisms, and Development of a Dosing Algorithm for Human Deposition Fraction", Journal of Occupational and Environmental Hygiene, https://doi.org/10.1080/15459624.2025.2602755

■ Background (Why important?)

• Understanding human exposure to harmful aerosol particles generated from various cigarette products is essential for public health research. Fine particles emitted from smoking and vaping can penetrate deep into the respiratory system, where they may cause cellular damage and increase the risk of respiratory diseases  (Figure a). Accurate characterization of these aerosol particles including their size distributions and regional deposition behavior is critical for assessing health risks and informing effective public health interventions.

■ Resluts (My contributions)

• Developed of Conventional Cigarette (CC) and Electronic Cigarette (EC) — contaning VAPE, Heat Not Burn (HNB), and Glycerin added Heat Not Burn (GHNB) — aerosol sampling system that mimics the inhalation-exhalation cycle of active smokers and stabilizes the transient puff flow for accurate aerosol measurement (Figure b). Through data analysis, we systematically defined the aerosolization mechanisms that govern the particle size distributions (PSDs) of CC, VAPE, HNB, and GHNB (Figure c). The results confirmed that physical mechanisms such as combustion, vaporization, and thermal decomposition are the primary determinants of PSDs

• Based on the PSDs (surface area concentrations:dS/dlogdp (Figure d)) of CC and EC aerosols and the deposition fractions in different regions of the human respiratory tract — including Extra-Thoracic (ET), Tracheo-Bronchial (TB), and Alveolar-Interstitial (AI) regions (Figure e) — we also developed a dosing algorithm per single puff for active smoker (Figure f). The results obtained through the dosing algorithm revealed that aerosol particles generated by CC and HNB exhibited the greatest level of accumulation in the human body, followed by GHNB, and VAPE.

• Finally, implemented online web desing tool for calculating deposition fraction in the ET, TB, and AI regions based on International Commission on Radiological Protection (ICRP) 1994 guideline (Figure g). By inputting various parameters, users can immediately observe how the trends and specific values of the deposition fraction change under different conditions.

    (Web Design Tool URL: https://sites.google.com/g.seoultech.ac.kr/nel/design-tool/lung-deposition-model)