Ligand design for multidimensional magnetic materials: a metallosupramolecular perspective
Bibliographic record
Abstract
The aim and scope of this review is to show the general validity of the 'complex-as-ligand' approach for the rational design of metallosupramolecular assemblies of increasing structural and magnetic complexity. This is illustrated herein on the basis of our recent studies on oxamato complexes with transition metal ions looking for the limits of the research avenue opened by Kahn's pioneering research twenty years ago. The use as building blocks of mono-, di- and trinuclear metal complexes with a novel family of aromatic polyoxamato ligands allowed us to move further in the coordination chemistry-based approach to high-nuclearity coordination compounds and high-dimensionality coordination polymers. In order to do so, we have taken advantage of the new developments of metallosupramolecular chemistry and in particular, of the molecular-programmed self-assembly methods that exploit the coordination preferences of metal ions and specifically tailored ligands. The judicious choice of the oxamato metal building block (substitution pattern and steric requirements of the bridging ligand, as well as the electronic configuration and magnetic anisotropy of the metal ion) allowed us to control the overall structure and magnetic properties of the final multidimensional nD products (n = 0-3). These species exhibit interesting magnetic properties which are brand-new targets in the field of molecular magnetism, such as single-molecule or single-chain magnets, and the well-known class of molecule-based magnets. This unique family of molecule-based magnetic materials expands on the reported examples of nD species with cyanide and related oxalato and dithiooxalato analogues. Moreover, the development of new oxamato metal building blocks with potential photo or redox activity at the aromatic ligand counterpart will provide us with addressable, multifunctional molecular materials for future applications in molecular electronics and nanotechnology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".