Influencing the Self‐Sorting Behavior of [2.2]Paracyclophane‐Based Ligands by Introducing Isostructural Binding Motifs
Bibliographic record
Abstract
Abstract Two isostructural ligands with either nitrile (Lnit) or isonitrile (Liso) moieties directly connected to a [2.2]paracyclophane backbone with pseudo‐meta substitution pattern have been synthesized. The ligand itself (Lnit) or its precursors (Liso) were resolved by HPLC on a chiral stationary phase and the absolute configuration of the isolated enantiomers was assigned by XRD analysis and/or by comparison of quantum‐chemical simulated and experimental electronic circular dichroism (ECD) spectra. Surprisingly, the resulting metallosupramolecular aggregates formed in solution upon coordination of [(dppp)Pd(OTf)2] differ in their composition: whereas Lnit forms dinuclear complexes, Liso exclusively forms trinuclear ones. Furthermore, they also differ in their chiral self‐sorting behavior as (rac)‐Liso undergoes exclusive social self‐sorting leading to a heterochiral assembly, whereas (rac)‐Liso shows a twofold preference for the formation of homochiral complexes in a narcissistic self‐sorting manner as proven by ESI mass spectrometry and NMR spectroscopy. Interestingly, upon crystallization, these discrete aggregates undergo structural transformation to coordination polymers, as evidenced by single‐crystal X‐ray diffraction.
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 | 0.000 |
| 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) | 0.001 | 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".