Developing Techniques for UV-visible Spectroscopy of Single Acoustically Levitated Aqueous Droplets for Applications in Atmospheric Chemistry
Bibliographic record
Abstract
Few studies have utilized UV-visible direct absorbance spectroscopy to probe acoustically levitated droplets, leading to a dearth of detailed procedures. Acoustically suspended droplets are an ideal contactless reaction compartment for investigating heterogeneous atmospheric chemistry. This is due to levitated droplets sharing similar properties to atmospheric droplets, such as high surface-area-to-volume-ratios. In this thesis, I describe a new apparatus and methodologies I developed to precisely control droplet evaporation, relative humidity, and atmospheric composition. The newly developed apparatus was used to investigate possible Brown Carbon (BrC) chemistry involving humic acid sodium salt, catechol, and water-soluble pine wood smoke extract, under variable atmospheres and illumination conditions. Results showed some deviation from bulk experiments, which may be attributed to pH changes inside levitated droplets, photochemical reactions, volatilization, and increased scattering. These results demonstrate that UV-visible direct absorbance spectroscopy of acoustically levitated droplets can be a powerful tool for studying atmospheric reactions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".