Predicting the relative humidities of liquid-liquid phase separation, efflorescence, and deliquescence of mixed particles of ammonium sulfate, organic material, and water using the organic-to-sulfate mass ratio of the particle and the oxygen-to-carbon elemental ratio of the organic component
Bibliographic record
Abstract
Abstract. Individual particles that on a mass basis consist dominantly of the components ammonium sulfate, oxygenated organic material, and water are a common class of submicron particles found in today's atmosphere. Here we use (1) the organic-to-sulfate (org:sulf) mass ratio of the overall particle and (2) the oxygen-to-carbon (O:C) elemental ratio of the organic component as input variables in parameterisations that predict the critical relative humidity of several different types of particle phase transitions. Specifically these variables were used to predict the critical relative humidity of liquid-liquid phase separation (SRH), efflorescence (ERH), and deliquescence (DRH). Experiments were conducted by optical microscopy for 11 different oxygenated organic-ammonium sulfate systems covering the range 0.1< org:sulf <12.8 and 0.29 < O:C < 1.33. These new data, in conjunction with other data already available in the literature, were used to develop the parameterisations SRH(org:sulf, O:C), ERH(org:sulf, O:C), and DRH(org:sulf, O:C). The parameterisations correctly predicted SRH within 15% RH for 88% of the measurements, ERH within 5% for 84% of the measurements, and DRH within 5% for 94% of the measurements. The applicability of the derived parameterisations beyond the training data set was tested against observations for organic-sulfate particles produced in an environmental chamber. The organic component consisted of secondary organic material produced by the oxidation of isoprene, α-pinene, and β-caryophyllene. The predictions of the parameterisations were also tested against data from the Southern Great Plains, Oklahoma, USA. The observed ERH and DRH values for both the chamber and field data agreed within 5% RH with the values predicted by the parameterisations using the measured org:sulf and O:C ratios as the input variables.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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 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".