On the stabilization of the carbonate dianion by sulfur dioxide
Bibliographic record
Abstract
The stabilization in the gas phase of the carbonate dianion [Formula: see text] by SO2 molecules is being investigated. The geometries of various isomers of [Formula: see text] (SO2)n and [Formula: see text] (SO2)n, for n = 1–4, have been optimized by the B3PW91/6−311+G(3df) method. Single-point CCSD and CCSD(T) energies at the DFT-optimized geometries were obtained for n = 1–3, using the 6−311+G(d) basis set. For n = 1 and 2, the monoanionic clusters are adiabatically more stable than the dianionic ones. However, starting at n = 3, they become less stable. The CCSD adiabatic electron detachment energy of the dianionic cluster switches from −0.39 eV for n = 2 to +0.20 eV for n = 3. The vertical electron detachment energy turns positive at n = 2, with a CCSD value of 1.35 eV. Several of the less stable dianionic, and most of the monoionic clusters, are characterized by the transfer of an oxygen atom from CO3 to SO2, forming [Formula: see text] or [Formula: see text] units, owing to [Formula: see text] + CO2 being more stable than [Formula: see text] + SO2. For the stabilization of the sulfate dianion by stepwise hydration, studied both experimentally and theoretically by other groups, a minimum of three water molecules was required.
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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 | 0.000 |
| 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".