Functionalization and cleavage of coordinated dinitrogen via hydroboration using primary and secondary boranes
Bibliographic record
Abstract
The reaction of the side-on, end-on ditantalum dinitrogen complex ([NPN]Ta)2(µ-η1:η2-N2)(µ-H)2 (where NPN = PhP(CH2SiMe2NPh)2) with a variety of secondary and primary boranes is reported. With 9-BBN, hydroboration of the Ta2N2 unit occurs via B-H addition, which in turn triggers a cascade of reactions that result in NN bond cleavage, ancillary ligand rearrangement involving silicon group migration, and finally elimination of benzene from the N-Ph group and a B-H moiety to generate the imidenitride derivative. In the presence of excess 9-BBN, the Lewis acid base adduct of the imidenitride ([NPµN]Ta(=NBC8H14)(µ-NB(H)C8H14)Ta[NPN]) is formed. A similar set of reactions is observed for dicyclohexylborane (Cy2BH), which hydroborates the dinitrogen complex to generate [NPN]Ta(H)(µ-η1:η2-NNBCy2)(µ-H)2Ta[NPN], followed by loss of H2 and silicon group migration to yield the imidenitride [NPµN]Ta(=NBCy2)(µ-N)(Ta[NPN]. With thexyl borane (H2BCMe2CHMe2), a similar sequence of reactions is suggested starting with hydroboration to generate [NPN]Ta(H)(µ-η1:η2-NNB(H)C6H13)(µ-H)2Ta[NPN], followed by loss of H2 and ancillary ligand rearrangement. When bis(pentafluorophenyl)borane (HB(C6F5)2) is used, no hydroboration of coordinated N2 is observed, rather simple adduct formation to give ([NPN]Ta)2(µ-η1:η2-NN-B(H)(C6F5)2)(µ-H)2 occurs. Key words: dinitrogen, tantalum, hydroboration, NN bond cleavage.
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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) | 0.003 | 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".