DFT studies of two-electron oxidation, photochemistry, and radical transfer between metal centres in the formation of platinum(<scp>iv</scp>) and palladium(<scp>iv</scp>) selenolates from diphenyldiselenide and metal(<scp>ii</scp>) reactants
Bibliographic record
Abstract
The oxidant diphenyldiselenide reacts with MIIMe2(bipy) (bipy = 2,2'-bipyridine) to form a pre-equilibrium involving weak adducts, from which [MMe2(bipy)]2·Ph2Se2 undergoes rate-limiting dissociation of phenylselenide preceded by the oxidative addition step to obtain [Me2(bipy)M-MMe2(bipy)(SePh)]+. Coordination of PhSe- gives the neutral MIII-MIII bonded dimers [MMe2(bipy)(SePh)]2. The dimers fragment in the presence of light to give radicals [MIIIMe2(bipy)(SePh)]˙. After reorientation in the solvent cage, the radicals interact to form triplet adducts [MIIIMe2(bipy)(SePh)·(bipy)MIIIMe2(SePh)]˙˙ with π-stacked 'SePh·bipy', followed by transformation via a Minimum Energy Crossing Point allowing [SePh]˙ transfer to give MIIMe2(bipy) and MIVMe2(bipy)(SePh)2. The regenerated MII reagent reacts with Ph2Se2 through the above sequence, allowing completion of reaction to give the MIV product only. The reaction of PtMe2(bipy) with diphenyldisulfide has been studied in an analogous manner to assist with interpretation of DFT results for reactions of diphenyldiselenide. In short, this study shows that photochemical cleavage of metal-metal bonds (Pd, Pt) via excitation to an M-M antibonding orbital facilates disproportionation of the MIII-MIII complex to MII and MIV complexes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".