Synthesis and attempted reductions of bulky 1,3,5-triazapentadienyl groups 2 and 13 halide complexes
Bibliographic record
Abstract
Three extremely bulky 1,3,5-triazapentadienes, ArNNNH (ArNNN = N{C(But)=N(Ar)}2; Ar = Mes (mesityl), Dep (2,6-diethylphenyl), or Dip (2,6-diisopropylphenyl)) have been prepared and structurally characterized. These are readily deprotonated, yielding a series of lithium and potassium triazapentadienyl complexes, one of which, (DipNNN)Li, has been structurally characterized. Similarly, three monomeric triazapentadienyl magnesium iodide complexes, (ArNNN)MgI(OEt2), and a dimeric calcium counterpart, {(MesNNN)Ca(THF)(μ-I)}2, have been prepared. Attempts to reduce the former gave homoleptic bis(triazapentadienyl) magnesium complexes, (ArNNN)2Mg (Ar = Mes or Dep) as the main products. One reaction also gave a very low yield of the magnesium(I) dimer, {(DepNNN)Mg–}2, which was structurally characterized. In related chemistry, two triazapentadienyl boron difluoride compounds, (ArNNN)BF2 (Ar = Mes or Dep), have been synthesized, and unsuccessful attempts have been made to reduce these to boron(I) heterocycles. For sake of comparison, attempts have been made to prepare a series of related amino-substituted β-diketiminato group 13 element(I) heterocycles. Although these were also not successful, several group 13 element(III) halide complexes incorporating this ligand class have been characterized.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".