Metal-Free Borylation of Heteroarenes Using Ambiphilic Aminoboranes: On the Importance of Sterics in Frustrated Lewis Pair C–H Bond Activation
Bibliographic record
Abstract
Two novel frustrated Lewis pair (FLP) aminoboranes, (1-Pip-2-BH 2 -C 6 H 4 ) 2 ( 2; Pip = piperidyl) and (1-NEt 2 -2-BH 2 -C 6 H 4 ) 2 ( 3; NEt 2 = diethylamino), were synthesized, and their structural features were elucidated both in solution and in the solid state. The reactivity of these species for the borylation of heteroarenes was investigated and compared to previously reported (1-TMP-2-BH 2 -C 6 H 4 ) 2 ( 1; TMP = tetramethylpiperidyl) and (1-NMe 2 -2-BH 2 -C 6 H 4 ) 2 ( 4; NMe 2 = dimethylamino). It was shown that 2 and 3 are more active catalysts for the borylation of heteroarenes than the bulkier analogue 1 . Kinetic studies and density functional theory calculations were performed with 1 and 2 to ascertain the influence of the amino group of this FLP-catalyzed transformation. The C–H activation step was found to be more facile with smaller amines at the expense of a more difficult dissociation of the dimeric species. The bench-stable fluoroborate salts of all catalysts ( 1F – 4F ) have been synthesized and tested for the borylation reaction. The new precatalysts 2F and 3F are showing higher reaction rates and yields for multigram-scale syntheses.
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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) | 0.001 | 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".