Radical–Radical Recognition: Switchable Magnetic Properties and Re-entrant Behavior
Bibliographic record
Abstract
π–π radical interactions have exacting geometry requirements, significantly more stringent than those of a hydrogen bond or a van der Waals interaction. Here, supramolecular synthons based on such radical–radical recognition are employed to generate switchable structural and magnetic properties. Interactions between neighboring paramagnetic ligands of the La(hfac) 3 (pyDTDA) 2 coordination complex cause a rare re-entrant phase transition (hfac = 1,1,1,5,5,5-hexafluoroacetylacetonato-; pyDTDA = 4-(2′-pyridyl)-1,2,3,5-dithiadiazolyl). Below 100 K, the complex is diamagnetic in the solid state, consistent with an f 0 lanthanum(III) ion and “pancake bonding” of the π-radical ligands. Upon heating, the supramolecular one-dimensional arrangement undergoes two sequential structural phase transitions, observed at ca. 160 and 310 K, successively involving the rupture of half and then the totality of the “pancake bonds” and generating stepwise increases in the paramagnetic susceptibility. We use the structural and magnetic data to develop a theoretical model that clearly predicts the unprecedented re-entrant behavior of this radical-La(III)-radical complex. Moreover, this microscopic free-energy model demonstrates that any system with essentially noninteracting “dimers” contains within itself the possibility of a distortion associated with re-entrant phase transitions if the lattice is “soft” enough (i.e., low rigidity).
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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 | 0.000 |
| 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".