Hygroscopic Growth, Phase Morphology, and Optical Properties of Model Aqueous Brown Carbon Aerosol
Bibliographic record
Abstract
Brown carbon aerosol in the atmosphere contain light-absorbing chromophores that influence the optical scattering properties of the particles. These chromophores may be hydrophobic, such as PAHs, or water soluble, such as nitroaromatics, imidazoles, and other conjugated oxygen-rich molecules. Water-soluble chromophores are expected to exist in aqueous solution in the presence of sufficient water and will exhibit physical properties (e.g., size, refractive index, and phase morphology) that depend on the environmental relative humidity (RH). In this work, we characterize the RH-dependent properties of 4-nitrocatechol (4-NC) and its mixtures with ammonium sulfate, utilizing a single-particle levitation platform coupled with Mie resonance spectroscopy to probe the size, real part of the complex refractive index (RI), and phase morphology of individual micron-sized particles. We measure the hygroscopic growth properties of pure 4-NC and apply mixing rules to characterize the growth of mixtures with ammonium sulfate. We report the RI at 589 nm for these samples as a function of RH and explore the wavelength dependence of the RI at non-absorbing wavelengths. The real part of the RI at 589 nm was found to vary in the range 1.54-1.59 for pure 4-NC from 92.5 to 75% RH, with an estimated pure component RI of 1.70. The real part of the RI was also measured for mixtures of AS and 4-NC and ranged from 1.39 to 1.51 depending on the component ratio and RH. We went on to characterize phase transitions in mixed particles, identifying the onset RH of liquid-liquid phase separation (LLPS) and efflorescence transitions. Mixtures showed LLPS in the range of 85-76% RH depending on the molar ratio, while efflorescence typically fell between 22 and 42% RH. Finally, we characterized the imaginary part of the complex RI using an effective oscillator model to capture the wavelength-dependent absorption properties of the system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".