Esterification of Octanoic Acid over Solid Acid Catalysts Derived from Petroleum Coke
Bibliographic record
Abstract
Petroleum coke (petcoke) is a solid waste of the oil industry, with limited use due to its high sulfur content (> 6.5 wt%) and other impurities. As a carbon-rich, abundant and inexpensive material, petcoke is a potential resource for carbon-based catalysts. Esterification is a broad, important class of reactions for which carbon-based catalysts have been investigated and applied successfully. The treatment of petcoke (functionalization) with different conditions of temperature, time, and types of acid incorporates surface groups, which are the active sites for the reaction. This study tested the catalytic performance of acid-modified petcoke samples over a model reaction: esterification of octanoic acid with methanol. A commercial catalyst, Amberlyst-15, was used for comparison. The effect of various parameters was evaluated, including stirring speed (200 - 800 rpm), temperature (40 - 80 °C), catalyst loading (1 - 4.5 wt%), and methanol-to-acid molar ratio (40:1 - 10:1). The selectivity of all catalysts was 100% towards the ester yield, with no byproducts from the reaction. The method for the evaluation of catalyst activities was based on kinetic parameters and turnover frequency. The catalytic activity of acidic petcoke samples was comparable to the commercial catalyst in terms of conversion with time at the same reaction conditions, and even higher on a per acid site basis. Based on those results, acid-modified petcoke is a prospective material for catalyzing esterification reactions. Different properties arise from the treatment of petcoke with strong acids. The number of strong acid sites, overall acid strength as well as the surface hydrophobicity all influence the catalytic performance for the esterification reaction. Leaching of active sites was problematic and resulted in almost complete deactivation of the petcoke-derived catalysts. An appropriate balance in the surface hydrophobicity/hydrophilicity and a strong attachment of the active sites to the petcoke surface are required for stability.
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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) | 0.001 | 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 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".