Synthesis, Characterization and Thermal Study of Divalent Germanium, Tin and Lead Triazenides for Atomic Layer Deposition
Bibliographic record
Abstract
The number of M–N bonded divalent group 14 precursors suitable for atomic layer deposition is limited, in particular for Ge and Pb. A majority of the reported precursors are dicoordinated, with the only tetracoordinated example being the Sn(II) amidinate. No such Ge(II) and Pb(II) compounds have been demonstrated. Herein, we present tetracoordinated Ge(II), Sn(II) and Pb(II) complexes bearing two sets of the bidentate 1,3-di-tert-butyl triazenide ligands. These compounds are highly volatile and show ideal behavior by thermogravimetric analysis. However, they have unusual thermal properties and exhibit instability during sublimation. Interestingly, the instability is not only temperature dependent but also facilitated by reduced pressure. Using quantum-chemical density functional theory, a gas-phase decomposition pathway was mapped out. The pathway account for the unusual thermal behavior of the compounds and is supported by electron impact mass spectrometry data.
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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".