Comprehensive Synthesis of Monohydroxy–Cucurbit[<i>n</i>]urils (<i>n</i> = 5, 6, 7, 8): High Purity and High Conversions
Bibliographic record
Abstract
We describe a photochemical method to introduce a single alcohol function directly on cucurbit[n]urils (n = 5, 6, 7, 8) with conversions of the order 95-100% using hydrogen peroxide and UV light. The reaction was easily scaled up to 1 g for CB[6] and CB[7]. Spin trapping of cucurbituril radicals combined with MS experiments allowed us to get insights about the reaction mechanism and characterize CB[5], CB[6], CB[7], and CB[8] monofunctional compounds. Experiments involving (18)O isotopically labeled water indicated that the mechanism was complex and showed signs of both radical and ionic intermediates. DFT calculations allowed estimating the Bond Dissociation Energies (BDEs) of each hydrogen atom type in the CB series, providing an explanation of the higher reactivity of the "equatorial" C-H position of CB[n] compounds. These results also showed that, for CB[8], direct functionalization on the cucurbituril skeleton is more difficult because one of the methylene hydrogen atoms (Hb) has its BDE lowering within the series and coming close to that of Hc, thus opening the way to other types of free radicals generated on the CB[8] skeleton leading to several side products. Yet CB[5]-(OH)1 and CB[8]-(OH)1, the first CB[8] derivative, were obtained in excellent yields thanks to the soft method presented here.
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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) | 0.002 | 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".