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Light-Driven Abiotic Formation of Dimethyl Selenyl Sulfide in the Liquid and Gas Phases

2025· article· en· W4407731439 on OpenAlexafffund
Paul A. Heine, Nadine Borduas‐Dedekind

Bibliographic record

VenueACS Earth and Space Chemistry · 2025
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaMitacs
KeywordsAbiotic componentDimethyl sulfideSulfideChemistryChemical engineeringEnvironmental scienceEnvironmental chemistryOrganic chemistryGeologyEngineeringSulfurPaleontology

Abstract

fetched live from OpenAlex

Biogenically produced volatile organic selenium (Se) species such as dimethyl selenyl sulfide (CH 3 SeSCH 3 ) and dimethyl diselenide (CH 3 SeSeCH 3 ) are important sources of Se in the atmosphere. Once emitted, Se can travel through the atmosphere and subsequently deposit to soils, impacting available Se in food crops. To improve the predictive capabilities of the sources and sinks of CH 3 SeSCH 3, we studied its abiotic light-driven formation and subsequent photochemical decay. Upon UVA irradiation of CH 3 SeSeCH 3 and its more abundant sulfur analogue, dimethyl disulfide (CH 3 SSCH 3 ), we observed the formation of CH 3 SeSCH 3 in both the liquid and gas phases. We unambiguously confirmed the synthesis of CH 3 SeSCH 3 by GC-MS and 1 H, 13 C, and 77 Se NMR spectroscopy before studying this process by online Vocus mass spectrometry in the gas phase. The photolysis by UVA light produced selenyl and thiyl radicals, which formed CH 3 SeSCH 3 in 36% yield. Moreover, we identified photo-oxidation products and subsequent SOA formation. Our mechanistic analysis concludes that the detection of CH 3 SeSCH 3 in the environment coexists with CH 3 SeSeCH 3 and CH 3 SSCH 3 . Thus, CH 3 SeSCH 3 in the environment, for example, above a phytoplankton bloom, may have a combination of both primary and secondary sources. Our study shines light on CH 3 SeSCH 3 ’s synthesis, isolation, and environmental transformations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.244
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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