Correlating Structural Features and <sup>207</sup>Pb NMR Parameters with the Stereochemical Activity of Pb<sup>II</sup> Lone Pairs in Birefringent Pb[2,6‐bis(benzimidazol‐2‐yl)pyridine] Complexes
Bibliographic record
Abstract
A series of PbII materials containing the highly anisotropic tridentate ligand 2,6‐bis(benzimidazol‐2‐yl)pyridine (bbp) and [Au(CN)2]–, Hg(CN)2 or halide bridging units, [Pb(bbp)Br2]·2H2O, Pb(bbp)I2, [Pb(bbp)I]2(µ‐I)[Au(CN)2], [Pb(bbp)Br]2(µ‐Br)[Au(CN)2], [Pb(bbp)Br2][Hg(CN)2], Pb(bbp)Cl[Au(CN)2]·0.25H2O and Pb(H2O)(bbp)2[Au(CN)2]2, have been prepared, structurally characterised and investigated spectroscopically by 207Pb solid‐state NMR spectroscopy. Of these, five possess similar coordination geometries, providing an ideal series to investigate structural parameters as indicators for stereochemical activity by correlation with the 207Pb chemical shift span parameter (Ω). The bond length of the substituent opposite to the stereochemically active lone pair and the angle between axial ligands were found to correlate weakly with Ω for these compounds (R2 = 0.85 and 0.66, respectively) and an expanded set of compounds with varying components and structures (R2 = 0.60 and 0.67, respectively), which indicates that these (or similar) structural parameters or Ω can be used to estimate the degree of lone‐pair activity. Compounds were also found to be highly birefringent with values ranging from 0.31(5) for Pb(H2O)(bbp)2[Au(CN)2]2 to 0.660(4) for [Pb(bbp)Br2]·2H2O, the latter being amongst the most birefringent compounds reported.
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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".