Not‐So‐Innocent Anions Determine the Mechanism of Cationic Alkylators
Bibliographic record
Abstract
Alkylating reagents based on thioimidazolium ionic liquids were synthesized and the influence of the anion on the alkylation reaction mechanism explored in detail using both experimental and computational methods. Thioimidazolium cations transfer alkyl substituents to nucleophiles, however the reaction rate was highly dependent on anion identity, demonstrating that the anion is not innocent in the mechanism. Detailed analysis of the computationally-derived potential energy surfaces associated with possible mechanisms indicated that this dependence arises from a combination of anion induced electronic, steric and coordinating effects, with highly nucleophilic anions catalyzing a 2-step process while highly non-nucleophilic, delocalized anions favor a 1-step reaction. This work also confirms the presence of ion-pairs and aggregates in solution thus supporting anion-induced control over the reaction rate and mechanism. These findings provide new insight into an old reaction allowing for better design of cationic alkylators in synthesis, gene expression, polymer science, and protein chemistry applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".