Application of positive matrix factor analysis in heterogeneous kinetics studies: an improvement to the mixed-phase relative rates technique
Bibliographic record
Abstract
Abstract. The mixed-phase relative rate approach for determining aerosol particle organic component heterogeneous reaction kinetics and OH uptake coefficients to particles is often performed utilizing mass spectral tracers as a proxy for particle phase reactant concentration. However, this approach may be influenced by signal contaminations from oxidation products during the experiment. In the current study, the mixed-phase relative rates technique has been improved by combining a Positive Matrix Factor (PMF) analysis with electron ionization Aerosol Mass Spectrometry, thereby removing the influence of m / z fragments from reaction products on the reactant signals. To demonstrate the advantages of this approach, the heterogeneous reaction between OH radicals and citric acid (CA) was investigated using a photochemical flow tube coupled to a compact time-of-flight aerosol mass spectrometer (C-ToF-AMS). The measured heterogeneous rate constant (k2) of citric acid toward OH was (3.31 ± 0.29) × 10−12 cm3 molecule−1 s−1 at 298 K and (30 ± 3)% RH and was ∼7.7 times greater than previously reported results utilizing individual m / z fragments. This phenomenon was further confirmed for particulate-phase organophosphates (TPhP, TDCPP, and TEHP), leading to k2 values significantly larger than previously reported. The results suggest that heterogeneous kinetics can be significantly underestimated when a non-molecular ion peak is used as the tracer. Finally, the results suggest that the heterogeneous lifetime of organic aerosol in models can be overestimated due to underestimated OH uptake coefficients, and that it may be necessary to revisit the heterogeneous kinetic data of organic aerosol components which were derived in the context of the relative rates technique.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".