Shape of sodium chloride particles as a function of drying rate
Bibliographic record
Abstract
Sodium chloride (NaCl) plays an important role both in the laboratory as a calibration aerosol and in nature as a component of sea-spray particles. Despite their ubiquity, NaCl particles show significant variation in their shape depending on the drying rate. This work builds on the current literature by establishing the influence of drying rate on the distribution of effective density and dynamic shape factor of laboratory generated NaCl particles. A calibration factor is first established using a spherical aerosol composed of Santovac (polyphenyl ether), to account for instrumental uncertainties. A total of three different drying rates were tested: −97 RH/s (slow), −260 RH/s (intermediate), and −506 RH/s (fast). The effective density and dynamic shape factor results (in the transition regime) shows that slow dried particles attained a distinct cube-like shape (ρeff ≈ 2200–1600 kg/m3, χ ≈ 1–1.15), intermediate particles achieved much rounded corners while still showing some cube-like features (ρeff ≈ 2200–1800 kg/m3, χ ≈ 1.00–1.08), and fast dried particles retained its spherical morphology (ρeff ≈ 2200–2000 kg/m3, χ ≈ 1.00–1.02). The range of shapes observed is also influenced by particle size; smaller particles (<50 nm) were more spherical regardless of the drying rate. Additionally, bidimensional effective density analysis revealed shape variability within particles of the same size, suggesting a distribution of morphologies, especially for the slow drying case. These results are validated using TEM images at three approximately different mobility sizes − 100, 200 and 400 nm.Copyright © 2025 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 | 0.000 | 0.000 |
| 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".