A vibrational spectroscopic study of the thermal behavior of Re<sub>2</sub>(CO)<sub>10</sub> on zeolite Y
Bibliographic record
Abstract
This work describes the thermal decomposition of Re2(CO)10 in zeolite Y, which generates the zeolite-supported complex Re0(CO)3(O-Z)3, where (O-Z) represents a framework oxygen. The adsorption and thermal decomposition of Re2(CO)10 was performed on dehydrated and hydrated zeolite NaY. The conversion to Re0(CO)3(O-Z)3 was not significantly affected by the presence of water within the supercages as the supported complex formed at around 200 °C no matter what the initial water content of the zeolite was. However, when the zeolite sample was treated at ≥200 °C for long periods, the adsorbed H2O became involved in the reactivity, playing a role as an oxidant. The subcarbonyl complex Re0(CO)3(O-Z)3 was oxidized, generating isolated Re2O7 or HReO4, or a mixture of both, which was dispersed inside the zeolite host. This result suggests that thermal decomposition of Re2(CO)10 on a hydrated zeolite under mild conditions can be a convenient route for preparation of zeolite-supported Re2O7 catalysts. Re0(CO)3(O-Z)3 was also formed in siliceous zeolite Y (SiY) upon heating. But it quickly decomposes into metal Re at around 200 °C, suggesting that the tricarbonyl species is destabilized in the almost natural zeolite framework. The present study also shows that FT-Raman spectroscopy is a useful technique for monitoring the behavior of the metal carbonyl species in zeolitic hosts.Key words: Raman spectroscopy, zeolite Y, rhenium carbonyl, rhenium oxide.
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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".