Performance of geopolymer as adsorbent on desulphurization of heavy gas oil
Bibliographic record
Abstract
Abstract Geopolymer is a porous aluminosilicate material and chemically similar to zeolites. As a low‐cost construction material, its suitability for adsorptive desulphurization (ADS) was studied using a petroleum feedstock. Geopolymer was produced by alkali activation of metakaolin and characterized by BET, NH 3 –TPD, SEM, FTIR, XRD, and XPS. The XRD and SEM studies evidenced the amorphous nature of geopolymer and the existence of macro‐ and mesopores. The XPS and NH 3 –TPD studies revealed the presence of surface Na and Al, and strong acid sites, respectively, in the prepared geopolymer. These sites interact with sulphur compounds of heavy gas oil through π ‐ π and acid–base interactions. The geopolymer showed a high sulphur adsorption capacity of 38.4 mg/g. The effects of adsorption parameters such as operating temperature, amount of adsorbent, and time for absorption on the adsorption capacity were examined using the Box–Behnken design statistical model. All three operating parameters significantly influenced the sulphur adsorption capacity of geopolymer. The adsorption of sulphur compounds on the geopolymer followed pseudo‐first‐order kinetics and did not affect its structural stability. Finally, the thermodynamic study revealed that adsorption of sulphur compounds on the geopolymer was spontaneous and exothermic.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".