Equilibrium studies of triphenyltin(IV) complexes with glycine, glycyl-glycine, and glycyl-glycyl-glycine in different aqueous solutions of ethanol
Bibliographic record
Abstract
The protonation equilibria of glycine (gly), glycyl-glycine (gly-gly), and glycyl-glycyl-glycine (gly-gly-gly) and their formation constants with triphenyltin(IV) chloride were studied over a wide pH range (pH 1–11), using a combination of spectrophotometric and potentiometric methods at constant temperature (25 °C), different ethanol–water mixtures (50%–80%, v/v), and constant ionic strength (0.1 mol dm–3 NaClO4). Least-squares regression calculations are consistent with the formation of ph3SnHL+, ph3SnL, and ph3SnH–1L– complex species, where L– represents the fully dissociated form of each ligand. The stability constant of the formed complexes in different media were analyzed in terms of Kamlet, Abboud, and Taft (KAT) parameters. Single-parameter correlations of the stability constants versus α (hydrogen-bond donor acidity), β (hydrogen-bond acceptor basicity), and for π* (dipolarity/polarizability) are relatively poor in all solutions, but multi-parameter correlations represent significant improvements with regard to the single- and dual-parameter models. Linear correlation is observed when the experimental logβxyz values are plotted versus the calculated ones, while all the KAT parameters are considered. Also, the stability constant values of the formed complexes are determined in zero percent of organic solvent using the Yasuda–Shedlovsky extrapolation approach. Finally, the results are discussed in terms of the effect of solvent on complexation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".