Thermal expansion of d10 dicyanometallate-based coordination polymers
Bibliographic record
Abstract
The thermal expansion of several new d10, dicyanometallate-based coordination polymers was examined by powder and single-crystal X-ray diffraction. In isostructural KNi[Au(CN)2]3, KCd[M(CN)2]3, and In[M(CN)2]3 (M=Ag(I), Au(I)), extremely large positive and negative thermal expansion (PTE/NTE) coefficients were discovered. Weaker metallophilic interactions promote larger PTE and NTE. Similarly, the M[Au(CN)2]2 series (M=Mn, Fe, Co, Zn, Hg) showed sizeable PTE and NTE effects. HgCN(NO3) exhibited similar behaviour, but significantly smaller PTE/NTE coefficients than the Ag and Au systems. Hg(CN)2 demonstrated entirely (anisotropic) PTE, partly attributed to a new structural mechanism resembling rigid unit modes in metal oxides. Hg(CN)2 is one of the first cyanide-containing frameworks not showing NTE. This work has demonstrated that Ag(I) and Au(I) in coordination polymers drive large expansivity, and when coupled with flexible cyanide frameworks, can also yield large NTE.
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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".