Effects of heating power and nicotine concentration on aerosol size distribution of a vaping device
Bibliographic record
Abstract
Vaping devices with a reduced heating power have the potential to generate less harmful chemicals. This leads the importance of examining particle size distribution (PSD) of undiluted aerosol at relatively lower power, which got a lesser attention to date. In this study, undiluted aerosol generated from a fourth-generation vaping device was measured using a low-flow (1 L/min) cascade impactor at heating powers ranging from 3.5 to 6.5 W with nicotine concentration of 12 and 18 mg/mL. The generated particle mass/puff increased with power linearly following a slope of 1.4. The particle diameter found was mostly within a range from 0.49 µm to 2.80 µm for the tested conditions. Higher generation of aerosol, either by increasing heating power or decreasing nicotine concentration, enhanced the transformation of particle size toward larger particles. A volumetric approach was used to estimate the percentile diameters corresponding to 10%, 50% and 90% of cumulative aerosols. The mass median aerodynamic diameter (MMAD) and geometric standard deviation (GSD) increased linearly up to 0.88 µm (with a slope of 0.082) and 1.53 (with a slope of 0.115), respectively, when the power increased from 3.5 to 5.5 W; and remained almost unchanged for power levels higher than 5.5 W. The nicotine effect on MMAD and GSD tended to diminish for a higher heating power of 5.5 W. Particle number was estimated from the measured particle mass, which can be useful to supplement particle number count measurements. These PSD data have potential implications for assessing viability of aerosol generating devices.Copyright © 2024 American Association for Aerosol Research
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".