Synthesis, Structures, and Multinuclear NMR Spectra of Tin(II) and Lead(II) Complexes of Tellurium-Containing Imidodiphosphinate Ligands: Preparation of Two Morphologies of Phase-Pure PbTe from a Single-Source Precursor
Bibliographic record
Abstract
Group 14 metal complexes of heavy chalcogen-centered anions, M[(TeP(i)Pr(2))(2)N](2) (5, M = Sn; 6, M = Pb) and M(TeP(i)Pr(2)NP(i)Pr(2)Se)(2) (7, M = Sn; 8, M = Pb), were synthesized in 64-89% yields by metathesis of alkali-metal salts of the ligands with group 14 metal dihalides. Crystallographic characterization of the complexes revealed that 5, 6, and 8 engage in metal...chalcogen secondary bonds to generate dimers, whereas 7 is monomeric in the solid state. Multinuclear ((1)H, (31)P, (77)Se, and (125)Te) solution NMR data for these homoleptic complexes evinced dynamic behavior leading to the equivalence of the two ligand environments. The Pb(II) complex 6 was utilized as a single-source precursor to micrometer-scale lead telluride particles via two divergent techniques: aerosol-assisted chemical vapor deposition of the complex in THF/CH(2)Cl(2) solution onto glass substrates yielded rectangular prisms, while solution injection of 6 in tri-n-octylphosphine onto Si/SiO(2)(100) substrates heated to 200-220 degrees C resulted in the formation of wires. PXRD and EDX analysis of the products confirmed the phase purity of the PbTe materials.
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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".