Carbon‐Supported Potassium Hydride for Efficient Low‐Temperature Desulfurization
Bibliographic record
Abstract
Abstract The industrial removal of organosulfur impurities from fossil fuels relies on transition‐metal‐based catalysts in harsh conditions (ca. 400 °C, up to 100 bar H2), yet desulfurization (DS) of refractory alkyl dibenzothiophenes (DBTs) remains challenging. Here, we report that carbon‐supported potassium hydride (KH/C) enables efficient DS of DBTs in mild conditions, viz. >97 % conversion of DBTs is achieved at 165 °C in 3–6 h while the yields of respective biphenyls are 84–95 % by using only 15 % excess of KH per a C−S bond. In addition, KH/C allows to lower the concentration of 4,6‐Me2DBT in the mesitylene solution from 1000 ppm to <3 ppm (165 °C, 20 h) and provides deoxygenation, denitrogenation and catalytic aromatic hydrogenation reactions. DS of various sulfur heterocycles by using KH/C, a transition‐metal‐free material based on earth abundant elements, is viable at low temperature and has prospects for the further development towards decentralized removal of organosulfur species from fossil fuels.
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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".