Gold−Gold Interactions as Crystal Engineering Design Elements in Heterobimetallic Coordination Polymers
Bibliographic record
Abstract
A series of coordination polymers containing Cu(II) and [Au(CN)(2)](-) units has been prepared. Most of their structures incorporate attractive gold-gold interactions, thus illustrating that such "aurophilic" interactions can be powerful tools for increasing structural dimensionality in supramolecular systems. [Cu(tren)Au(CN)(2)][Au(CN)(2)] (1, tren = tris(2-ethylamino)amine) forms a cation/anion pair, which is weakly linked by hydrogen bonds but not by aurophilic interactions. [Cu(en)(2)Au(CN)(2)][Au(CN)(2)] (2-Au, en = ethylenediamine) is a 2-D system composed of a chain of [Au(CN)(2)](-) anions and another chain of [(en)(2)Cu-NCAuCN](+) cations; short Au-Au bonds of 3.1405(2) A connect the anions. This bond is shorter than that observed in the analogous silver(I) structure, 2-Ag. The average M-C bond lengths of 1.984(8) A in 2-Au are significantly shorter than those found in 2-Ag, suggesting that Au(I) is smaller than Ag(I). Cu(dien)[Au(CN)(2)](2) (3, dien = diethylenetriamine) forms a 1-D chain of tetranuclear [Au(CN)(2)](-) units that are bound to [Cu(dien)] centers. Aurophilic interactions of ca. 3.35 A hold the tetramer together. Cu(tmeda)[Au(CN)(2)](2) (4, tmeda = N,N,N',N'-tetramethylethylenediamine) forms a 3-D network by virtue of aurophilic interactions of 3.3450(10) and 3.5378(8) A. Altering the Cu:Au stoichiometry yields Cu(tmeda)[Au(CN)(2)](1.5)(ClO(4))(0.5) (5), which has an unusual 2-D rhombohedral layer structure (space group R32). Complex 5 is composed of three mutually interpenetrating Cu[Au(CN)(2)](1.5) networks which are interconnected by aurophilic interactions of 3.4018(7) and 3.5949(8) A. Weak antiferromagnetic coupling is observed in 2 and 5.
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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) | 0.000 | 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) | 0.001 | 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".