A DFT study of spherands containing five anisyl groups — Highly preorganized to bind the alkali metal
Bibliographic record
Abstract
Although anisyl units are basically poor ligands for metal ions, the rigid placements of their oxygens during synthesis rather than during complexation are undoubtedly responsible for the enhanced binding and selectivity of the spherand. We used standard B3LYP/6-31G** (5d) density functional theory (DFT) to investigate the complexation between spherands containing five anisyl groups, with CH 2 –O–CH 2 (2) and CH 2 –S–CH 2 (3) units in an 18-membered macrocyclic ring, and the cationic guests (Li + , Na + , and K + ). Our geometric structure results for spherands 1, 2, and 3 are in good agreement with the previously reported X-ray diffraction data. The absolute values of the binding energy of all the spherands are inversely proportional to the ionic radius of the guests. The results, taken as a whole, show that replacement of one anisyl group by CH 2 –O–CH 2 (2) and CH 2 –S–CH 2 (3) makes the cavity bigger and less preorganized. In addition, both the binding and specificity decrease for small ions. The spherands 2 and 3 appear beautifully preorganized to bind all guests, so it is not surprising that their binding energies are close to the parent spherand 1. Interestingly, there is a clear linear relation between the radius of the cavity and the binding energy (R 2 = 0.999).Key words: spherands, preorganization, density functional theory, binding energy, cavity size.
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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 | 0.001 | 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 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".