Investigating the photosensitized chemistry of proxies for tropospheric brown carbon
Bibliographic record
Abstract
• The brown carbon proxy 1,4-naphthoquinone generates reactive triplet states that act as potent endogenous oxidants in aqueous aerosols, efficiently abstracting hydrogen from organic compounds with a kinetic hierarchy (alkanes < oxygenated alkanes < phenols) governed by bond dissociation energy (BDE) and oxidation potential (OP). This self-amplifying, oxygen-independent photochemical mechanism represents a key pathway for secondary organic aerosol growth under haze conditions. Brown carbon (BrC) profoundly influences secondary organic aerosol (SOA) formation via photosensitized reactions in atmospheric condensed phases, yet the intrinsic oxidative power of its excited triplet state remains mechanistically unresolved. We reveal that the BrC proxy 1,4-naphthoquinone (NQ) undergoes dual photochemical pathways in deoxygenated aqueous systems, simultaneous self-photoconversion and substrate oxidation, enabled by two distinct, long-lived triplet states ( 3 NQ* and 3 OH-NQ*) with 3 (n, π*) configurations generated under 355 nm irradiation. Crucially, 3 NQ* acts as an endogenous oxidant, driving efficient hydrogen abstraction from key organic classes without requiring external oxidants. Oxidation kinetics exhibit a striking hierarchy governed by bond dissociation energies and one-electron oxidation potentials: alkanes (10 4 M −1 s −1 ) < oxygenated alkanes (10 5 M −1 s −1 ) < phenols (10 6 M −1 s −1 ). Radical intermediates (alkyl, alkoxyl, phenoxy) dehydrogenate into stable products (e.g., benzoquinone from phenol), while the self-photoconversion product OH-NQ regenerates a secondary triplet ( 3 OH-NQ*), amplifying oxidative cascades. This establishes 3 BrC* as the dominant sink for phenols in BrC-rich haze, particularly under acidic, O 2 -limited conditions. Our findings provide kinetic and mechanistic benchmarks for integrating triplet-state chemistry into atmospheric models, advancing predictions of SOA formation in regions plagued by severe particulate pollution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".