Thermodynamic Properties of Gaseous Selenium Species of Atmospheric Interest
Bibliographic record
Abstract
Selenium (Se) is an essential element for fauna, flora, and human health. Up to a third of Se can cycle through the atmosphere. The volatile organic Se species include dimethyl selenide (CH 3 SeCH 3 ), dimethyl diselenide (CH 3 SeSeCH 3 ), and methaneselenol (CH 3 SeH), and will undergo rapid atmospheric oxidation. To better constrain the fate of atmospheric Se compounds, high-level ab initio electronic structure calculations were performed to estimate the thermodynamic properties of 11 gaseous Se species (HSe •, H 2 Se, CH 2 Se, CH 3 SeH, • CH 2 SeH, CH 3 Se •, CH 3 SeSe •, CH 3 SeCH 3, CH 3 Se • CH 2, CH 3 SeSeCH 3, and CH 3 SeSe • CH 2 ) using their atomization reactions. Several corrections were applied to provide highly accurate calculated standard enthalpies of formation at 298 K, Δ f H° 298 K . Standard molar entropy at 298 K, S ° 298 K, and heat capacity, C p ( T ) over the temperature range 300–1500 K, from vibrational, translational, and external rotation contributions were computed using statistical thermodynamics based on the vibrational frequencies and structures obtained at the CCSD(T)/aVTZ level of theory. Hindered rotational contributions to S ° 298 K and C p (T) were calculated from the energy levels, where the internal rotation potential was calculated at the MP2/aVTZ level of theory. The bond dissociation energies at 298 K for H–Se, Se–Se, and C–Se bonds in the Se molecules were derived from their calculated Δ f H° 298 K values. The same protocol was applied to O and S species for comparison with Se. Their Δ f H° 298 K, S ° 298 K, and C p (T) values were in good agreement with the corresponding available literature data. This work provided the first thermodynamic properties for the organic Se species. The data obtained in this work could be used in chemical-transport models to assess the fate of atmospheric Se and its speciation unravelling the Se biogeochemical cycles.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".