2004 Alcan Award LectureFrom dinuclear to triakontahexanuclear complexes Adventures in supramolecular coordination chemistry
Bibliographic record
Abstract
Polynuclear coordination complexes result from the interplay between the arrangement of the binding sites of a ligand, and their donor content, and the coordination preferences of the metal ion involved. Rational control of the ligand properties, such as denticity, geometry, and size, can lead to large, and sometimes predictable, polynuclear assemblies. This Alcan Award Lecture highlights our "adventures" with polynucleating ligands over the last 25 years, with examples ranging from simple dinucleating to more exotic high-denticity ligands. Complexes with nuclearities ranging from 2 to 36 have been produced, many of which have novel magnetic, electrochemical, and spectroscopic properties. Self-assembly strategies using relatively simple "polytopic" ligands have been very successful in producing high-nuclearity clusters in high yield. For example, linear "tritopic" ligands produce M9 (M = Mn(II), Fe(II), Fe(III), Co(II), Ni(II), Cu(II), Zn(II)) [3 × 3], flat grid-like molecules, which have quantum dot-like arrays of nine closely spaced metal centers in electronic communication. Some of these grids are discussed in terms of their novel magnetic and electrochemical properties, and also as multistable nanometer-scale platforms for potential molecular device behaviour. Bigger ligands with extended arrays of coordination pockets, and the capacity to self-assemble into much larger grids, are highlighted to illustrate our current and longer term goals of generating polymetallic molecular two-dimensional layers on surfaces.Key words: Alcan Award Lecture, transition metal, polynuclear, structure, magnetism, electrochemistry, surface studies, molecular device.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.050 | 0.014 |
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".