Thermal Stability and Decomposition Pathways in VolatileMolybdenum(VI) Bis-Imides
Bibliographic record
Abstract
The vapor deposition of many molybdenum-containing films relies on the delivery of volatile compounds with the general bis(tert-butylimido)molybdenum(VI) framework, both in atomic layer deposition and chemical vapor deposition. We have prepared a series of (tBuN)2MoCl2 adducts using neutral N,N’-chelates and investigated their volatility, thermal stability, and decomposition pathways. Volatility has been determined by thermogravimetric analysis, with the 1,4-di-tert-butyl-1,3-diazabutadiene adduct (5) found to be the most volatile (1 Torr of vapor pressure at 135 ºC). Thermal stability was measured primarily using differential scanning calorimetry, and the 1,10-phenanthroline adduct (4) was found to be the most stable, with an onset of decomposition of 303 ºC. We have also investigated molybdenum compounds with other alkyl-substituted imido groups: these compounds all follow a similar decomposition pathway, γ-H activation, with varying reaction barriers. The tert-pentyl, 1-adamantyl, and a cyclic imido (from 2,5-dimethylhexane-2,5-diamine) were systematically studied to probe the kinetics of this pathway. All of these compounds have been fully characterized, including via single-crystal X-ray diffraction, and a total of 19 unique structures are 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".