Surface studies of magnesium oxide‐based catalysts modified with X <sub>2</sub> or MgX <sub>2</sub> (X = Br, I)
Bibliographic record
Abstract
The introduction of a halide (Br, I) onto MgO leads to obtaining catalysts whose catalytic activity in transfer hydrogenation of acrolein with ethanol is significantly higher than that of unmodified MgO. In data found in literature, there is no concise view on how the modification of the surface of MgO with a halide affects its surface properties. Although most of the literature studies indicate a dependence of activity on the initial halide‐containing compound and type of halide, no study comprising both these aspects has been performed. The aim of the present study was to conduct measurements of MgO modified with two halides and with two types of initial halide‐containing compounds with surface‐sensitive techniques to determine how each of these factors influences the surface properties of the catalyst. Titration experiments showed that all of the modified catalysts have a smaller diversity of basic site strengths than unmodified MgO. They also revealed that for all studied systems, the modification of the surface leads to the formation of Brønsted acidic sites, which MgO does not possess. XPS spectra indicate that bromine‐modified catalysts give a broader range of surface species than the appropriate iodine‐modified ones. Moreover, they showed that in the case of both iodine‐modified and bromine‐modified catalysts, the one that exhibited the higher concentration of the appropriate halogen on the surface showed a lower activity in catalytic transfer hydrogenation of acrolein with ethanol. Copyright © 2015 John Wiley & Sons, Ltd.
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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".