Mesoporous Adsorbents for Desulfurization of Model Diesel Fuel: Optimization, Kinetic, and Thermodynamic Studies
Bibliographic record
Abstract
Mesoporous alumina-based adsorbents consisting of a π-electron acceptor complexing agent (2,7-dinitro-9-fluorenone) were synthesized and characterized. Adsorbents were screened for the removal of sulfur compounds from a model ultra-low-sulfur diesel fuel via a charge transfer complex (CTC) mechanism. The sulfur adsorption isotherms and kinetics were examined. The kinetics of sulfur adsorption followed a pseudo-second-order model with the CTC adsorbents. Among the three adsorbents screened, a commercial γ-Al2O3 CTC adsorbent showed the highest desulfurization in a short-run period. The regeneration of spent adsorbent was studied with three different polar solvents, namely chloroform, dichloromethane, and carbon tetrachloride. Dichloromethane was found to be the most suitable solvent for extracting a major portion of sulfur compounds occupied in the pores of the spent adsorbent. γ-Al2O3 CTC adsorbent can be reused after regeneration. Thermodynamic parameters such as Ea, ΔG, ΔH, and ΔS provided a better insight into the adsorption process.
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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) | 0.000 | 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 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".