Synthesis of a hindered <i>C</i><sub>2</sub>-symmetric hydrazine and diamine by a crisscross cycloaddition of citronellal azine
Bibliographic record
Abstract
Crisscross cycloaddition of citronellal azine (6) with 2 equiv. of TFA and powdered 3 Å molecular sieves in CH2Cl2 at reflux for 22 h afforded 37% of the desired C2-symmetric hydrazine 7 and 5%–10% of diastereomer 8 in which one of the 6–5 ring fusions is cis. Methylation of the hydrazine of 7 and reduction of the resulting salt (9) with Li in NH3 cleaved the N—N bond to give secondary tertiary amine 10 in 97% yield. Eschweiler–Clarke methylation afforded the C2-symmetric bis tertiary amine 11 in 69% yield. Racemic products were obtained in initial attempts at asymmetric catalysis using 7 or 11 as asymmetric bases, using bistertiary amine 11 as a ligand analogous to sparteine for alkyllithiums, or using the lithium amide from secondary tertiary amine 10 as an asymmetric base. Apparently, the proton is buried in the core of 11, leaving a hydrophobic surface; the free counterion is not an asymmetric catalyst. Diamine 11 may be too hindered to complex to s-BuLi. Tertiary amine 11 (pKa1 = 24.7) is more basic than DBU (pKa = 24.3) in CH3CN, in good agreement with theory.Key words: crisscross cycloaddition, azine, dipolar cycloaddition, calculation of pKa.
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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 | 0.001 |
| 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".