Nitric Acid Functionalization of Petroleum Coke to Access Inherent Sulfur
Bibliographic record
Abstract
Sulfonated carbon-based catalysts have been identified as promising solid acid catalysts, and petroleum coke (petcoke), a byproduct of the oil industry, is a potential feedstock for these catalysts. In this study, sulfur-containing (6.5 wt%) petcoke was used as a precursor for these catalysts through direct functionalization (i.e., without an activation step) with nitric acid to access the inherent sulfur. Catalysts were also prepared using sulfuric acid and a mixture of nitric and sulfuric acid (1:3 vol ratio). Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and titration were used to identify and quantify the acid sites. The activities of the prepared catalysts were determined for the esterification of octanoic acid with methanol. Petcoke had few −SO3H groups, and correspondingly no catalytic activity for the reaction. All acid treatments increased the number of −SO3H groups and promoted esterification. Treatment with nitric acid alone resulted in the oxidation of the inherent sulfur in petcoke to produce ~0.7 mmol/g of strong acid sites and a total acidity of 5.3 mmol/g. The acidity (strong acid and total) was lower with sulfuric acid treatment but this sample was more active for the esterification reaction (TOF of 31 h−1 compared to 7 h−1 with nitric acid treatment).
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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".