Predicting speciation in the multi-component equilibrium self-assembly of a metallosupramolecular complex
Bibliographic record
Abstract
A practical method to predict the speciation in a multi-component equilibrium self-assembly process has been developed and applied to the formation of the square macrocyclic complex formed from (ethylenediamine)Pd(II) and 4,4′-bipyridyl. The method is based on an additive free energy approach that derives the cumulative formation constants of all 56 species at equilibrium from a set of five pair-wise interactions. Estimates for the required values of the pair-wise interactions were derived from potentiometric titration of (ethylenediamine)Pd(II) and 3-phenylpyridine, and from (diethylenetriamine)Pd(II) and 4,4′-bipyridyl systems. The method calculates the equilibrium speciation as a function of reactant concentrations and pH and produces a map of the range of compositions in which the square complex and competing species are dominant. The predictions of the method closely correlate with available experimental data.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".