Analytical optical methods for measuring organic peroxides and hydroperoxides: An evaluation
Bibliographic record
Abstract
Hydrogen peroxide, organic peroxides and hydroperoxides exhibit high reactivity and play a pivotal role in atmospheric chemistry. These compounds are formed during the oxidation of volatile organic compounds in both gaseous and aqueous phases, particularly under low NOx conditions. Their significant contribution to the mass of secondary organic aerosols (SOA) is well-documented, and they are believed to have significant health implications. Several spectrophotometric methods have been employed to measure SOA-bound peroxides in laboratory samples, but systematic comparisons are lacking. In this study, we have assessed the advantages and limitations of these methods, including the traditional and microwave-assisted iodometric methods, the 4-nitrophenyl boronic acid assay (NPBA), and the Fenton reaction-assisted ferrous-xylenol (FOX2) assay. Besides, a comprehensive evaluation of these methodologies was conducted for the first time across a substantial cohort of commercial peroxides and hydroperoxides, employing diverse solvents (namely, water, 1-propanol, acetonitrile, methanol and chloroform) to provide broader insights compared to previous work. Ultimately, the four methods were applied and compared for peroxide determination in laboratory-generated SOA resulting from gas-phase ozonolysis of a-pinene. This study opens new opportunities for future mechanistic investigation into SOA formation and reactivity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".