Neutral Chiral Tetrakis‐Iodo‐Triazole Halogen‐Bond Donor for Chiral Recognition and Enantioselective Catalysis
Bibliographic record
Abstract
Halogen bonding represents a powerful tool in the field of noncovalent interactions. However, applications in enantioselective recognition and catalysis remain almost nonexistent, due in part to the distinct features of halogen bonds, including long covalent and noncovalent bond distances and high directionality. Herein, this work presents a novel chiral tetrakis-iodo-triazole structure as a neutral halogen bond donor for both chiral anion-recognition and enantioinduction in ion-pair organocatalysis. NMR-titration studies revealed significant differences in anion affinity between the halogen bonding receptor and its hydrogen bonding parent. Selective recognition of chiral dicarboxylates and asymmetric induction in a benchmark organocatalytic reaction were demonstrated using the halogen bond donor. Inversions in the absolute sense of chiral recognition, enantioselectivity, and chiroptical properties relative to the related hydrogen donor were observed. Computational modeling suggested that these effects were the result of distinct anion-binding modes for the halogen- versus hydrogen-bond donors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 teacher head, 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".