Solvent effects on ion pairing of tetra‐<i>n</i>‐butylammonium cyanide. A conductometric study
Bibliographic record
Abstract
Abstract Tetra‐n‐butylammonium cyanide (n‐Bu4NCN) is a commonly used reagent, for example, for the synthesis of nitriles. Recently n‐Bu4NCN has been used as the nucleophilic reagent in kinetic isotope effect studies of nucleophilic aliphatic substitution reactions. The present research concerns the aggregation status (dissociated ions, ion pairs, higher aggregates) and transport properties of n‐Bu4NCN in water, dimethyl sulfoxide (DMSO), and tetrahydrofuran (THF), at 25°C as studied by means of precision conductometry. These properties are of great importance since both non‐polar and dipolar aprotic solvents are commonly used in the applications. In water as solvent the equilibrium constant for ion‐pair formation, Kp = 10.1 and the limiting molar conductivity, Λo = 102.4 cm2 Ω−1 mol−1. The corresponding values for DMSO are Kp = 1.98 ± 0.19 and Λo = 34.59 ± 0.03 cm2 Ω−1 mol−1. These data imply that the degree of dissociation, in contrast to the expectations, is higher in DMSO than in water at the same salt concentration. In THF, the conductance as a function of concentration shows a minimum typical for solvents with low relative permittivity, indicating the formation of higher aggregates. The equilibrium constant for ion‐pair formation and conductivity in THF is Kp = 58.4 × 103 and Λo = 9.81 cm2 Ω−1 mol−1. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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 | 0.000 | 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".