Iodide effects in transition metal catalyzed reactions
Bibliographic record
Abstract
The unique properties of I(-) allow it to be involved in several different ways in reactions catalyzed by the late transition metals: in the oxidative addition, the migration, and the coupling/reductive elimination steps, as well as in substrate activation. Most steps are accelerated by I(-)(for example through an increased nucleophilicity of the metal center), but some are retarded, because a coordination site is blocked. The "soft" iodide ligand binds more strongly to soft metals (low oxidation state, electron rich, and polarizable) such as the later and heavier transition metals, than do the other halides, or N- and O-centered ligands. Hence in a catalytic cycle that includes the metal in a formally low oxidation state there will be less tendency for the metal to precipitate (and be removed from the cycle) in the presence of I(-) than most other ligands. Iodide is a good nucleophile and is also easily and reversibly oxidized to I(2). In addition, I(-) can play key roles in purely organic reactions that occur as part of a catalytic cycle. Thus to understand the function of iodide requires careful analysis, since two or sometimes more effects occur in different steps of one single cycle. Each of these topics is illustrated with examples of the influence of iodide from homogeneous catalytic reactions in the literature: methanol carbonylation to acetic acid and related reactions; CO hydrogenation; imine hydrogenation; and C-C and C-N coupling reactions. General features are summarised in the Conclusions.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".