Gas phase dehydration of glycerol to acrolein over NaHSO<sub>4</sub>@Zr‐MCM‐41 catalyst
Bibliographic record
Abstract
ABSTRACT The NaHSO 4 @Zr‐MCM‐41 catalyst modified by dodecyltrimethoxysilane (DTMS) showed excellent performance during the dehydration of glycerol to acrolein. The glycerol conversion and acrolein selectivity and yield on NaHSO 4 ‐DTMS@Zr‐MCM‐41 (Cat‐2) are higher than that of NaHSO 4 @Zr‐MCM‐41 (Cat‐1). The dispersity of NaHSO 4 is remarkably improved by an appropriate amount of DTMS modification on Cat‐2 because of the steric effect between DTMS and NaHSO 4 . Therefore, the total acidic amount of Cat‐2 is more than that of Cat‐1, but its acidic intensity is weaker than that of Cat‐1. The more total amount of acidity is beneficial to improve the glycerol conversion, and weaker acid strength leads to less carbon deposition. The amount of Brønsted acid sites is more than that of Cat‐1; however, the amount of Lewis acid sites is less, so the B/(B + L) of Cat‐2 is higher, which is beneficial and improves the acrolein selectivity. The Cat‐2 catalyst has proper hydrophobicity by grafting the silane group on the support surface, which can suppress the leaching of NaHSO 4 because the water that existed in the glycerol aqueous solution and that was produced in the reaction is not easily adsorbed on the catalyst surface. The appropriate hydrophobicity is beneficial to the quick desorption of products, which can also suppress the coke formation. The stability of Cat‐2 is obviously higher than that of Cat‐1 because the coke that was deposited and the S elemental leaching on Cat‐1 are more serious than that of Cat‐2. The reaction pathway of the dehydration of glycerol was proposed, and the reaction conditions were optimized on the Cat‐2 catalyst.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".