Palladium Nanoparticle Size Effect in Hydrodesulfurization of 4,6‐Dimethyldibenzothiophene (4,6‐DMDBT)
Bibliographic record
Abstract
Abstract Pd nanoparticle size sensitivity of 4,6‐dimethyldibenzothiophene (4,6‐DMDBT) hydrodesulfurization was investigated by using 4, 8, 13, and 87 nm particles and was compared with the sulfur‐free and sulfur‐inhibited hydrogenation of 3,3‐dimethylbiphenyl, which is a product of direct desulfurization of 4,6‐DMDBT. The smallest 4 nm particles provided unprecedented (for Pd at 5 MPa and 300 °C) direct desulfurization selectivity of 20 % at 40 % conversion because of the reduced contribution of the hydrogenation path. The 4 nm particles were poisoned by the adsorbed sulfur to the greatest extent. The optimal size, providing the highest Pd mass‐based yield of the desulfurized products, was found to be 8 nm. The catalyst with 87 nm particles was based on Pd nanocubes with the lowest edge/terrace surface atom ratio and large terraces and this showed the lowest sulfur extraction from both 4,6‐DMDBT and sulfurous intermediates as a result of the low availability of edge atoms for a perpendicular sigma‐mode adsorption through the lone pair of the sulfur atom.
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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 | 0.001 |
| 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".