Temperature effects on xanthone–β-cyclodextrin binding dynamics
Bibliographic record
Abstract
The complexation dynamics of the triplet excited state of xanthone with β-cyclodextrin were studied at various temperatures between 10 and 50 °C. Association and dissociation rate constants were determined using the laser flash photolysis quenching methodology with Cu2+ as a quencher. The rate constants for the association and dissociation of triplet xanthone with β-cyclodextrin increased with temperature, while the equilibrium constant for the triplet excited state remained relatively constant. Equilibrium constants for the ground-state complexation of xanthone with β-cyclodextrin were determined from fluorescence studies at various temperatures. The ground-state binding efficiency decreased with temperature and was markedly greater than that of the triplet excited state at all temperatures. The enthalpy and entropy for the β-cyclodextrin complex formation of the ground and triplet excited states fall on the enthalpy–entropy compensation relationship previously established for cyclodextrin complexes. The activation enthalpies for the association and dissociation rate constants for triplet xanthone are similar. The activation entropy is favorable for the association process, whereas a negative activation entropy was measured for the dissociation process, suggesting that solvation plays a key role in the complex formation between xanthone and β-cyclodextrin.
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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) | 0.002 | 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".