Surfactant Partitioning Dynamics in Freshly Generated Aerosol Droplets
Why this work is in the frame
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Bibliographic record
Abstract
Aerosol droplets are unique microcompartments with relevance to areas as diverse as materials and chemical synthesis, atmospheric chemistry, and cloud formation. Observations of highly accelerated and unusual chemistry taking place in such droplets have challenged our understanding of chemical kinetics in these microscopic systems. Due to their large surface-area-to-volume ratios, interfacial processes can play a dominant role in governing chemical reactivity and other processes in droplets. Quantitative knowledge about droplet surface properties is required to explain reaction mechanisms and product yields. However, our understanding of the compositions and properties of these dynamic, microscopic interfaces is poor compared to our understanding of bulk processes. Here, we measure the dynamic surface tensions of 14-25 μm radius (11-65 pL) droplets containing a strong surfactant (either sodium dodecyl sulfate or octyl-β-D-thioglucopyranoside) using a stroboscopic imaging approach, enabling observation of the dynamics of surfactant partitioning to the droplet-air interface on time scales of 10s to 100s of microseconds after droplet generation. The experimental results are interpreted with a state-of-the-art kinetic model accounting for the unique high surface-area-to-volume ratio inherent to aerosol droplets, providing insights into both the surfactant diffusion and adsorption kinetics as well as the time-dependence of the interfacial surfactant concentration. This study demonstrates that microscopic droplet interfaces can take up to many milliseconds to reach equilibrium. Such time scales should be considered when attempting to explain observations of accelerated chemistry in microcompartments.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it