Mechanistic Insights into I <sub>2</sub> O <sub>5</sub> Heterogeneous Hydrolysis and Its Role in Iodine Aerosol Growth in Pristine and Polluted Atmospheres
Bibliographic record
Abstract
Abstract. Higher iodine oxides are intricately linked to marine aerosol formation; however, the underlying physicochemical mechanisms remain poorly constrained, particularly for I2O5, which is stable yet conspicuously absent in the atmosphere. While reactivity with water has been implicated, the direct hydrolysis of I2O5 (I2O5 + H2O → 2HIO3) fails to account for this discrepancy due to its high activation barrier (21.8 kcal mol-1). Herein, we have probed heterogeneous hydrolysis of I2O5 mediated by prevalent chemicals over oceans through Born-Oppenheimer molecular dynamics and well-tempered metadynamics simulations. Our results demonstrate that self-catalyzed pathways involving I2O5 and its hydrolysis product HIO3 substantially reduce the reaction barrier, thereby accelerating the conversion of I2O5 to HIO3 in pristine marine environments. In polluted regions, interfacial hydrolysis of I2O5 mediated by acidic or basic pollutants (e.g., H2SO4 or amines) proceeds with even greater efficiency, characterized by remarkably low barriers (≤1.3 kcal mol-1). Collectively, these proposed heterogeneous reactions of I2O5 are highly effective, acting as a hitherto unrecognized sink for I2O5 and a source of HIO3—processes that facilitate marine aerosol growth and rationalize the high iodate abundances detected in aerosols. These findings provide mechanistic insight into the elusive I2O5-to-HIO3 conversion, offering a critical step toward improving the representation of iodine chemistry and marine aerosol formation in atmospheric models, with implications for climate prediction and environmental impact assessment.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".