Improved <scp> H <sub>2</sub> SO <sub>4</sub> </scp> ‐catalyzed alkylation reaction in a rotating packed bed reactor by adding additives
Bibliographic record
Abstract
Abstract The isobutane/butene alkylation process catalyzed by an acid solution is widely used to obtain high octane number gasoline components. However, limited by the mass transfer and mixing of the acid solution and the hydrocarbon liquid–liquid system, the product performance needs to be improved. Here, the alkylation reaction was strengthened by combining the chemical regulation of the reactant system and process intensification. Three homologs of sulphates and two hydrophilic surfactants were used as additives to regulate the properties of the acid solution, and the effect of different additives on isobutane/butene alkylation was investigated in a rotating packed bed. The Hammett acidity and solubility of isobutane in acid solutions with different additives were measured, and their synergistic effects on alkylation performance were explored. Under relatively mild conditions (the reaction at 8°C and an isobutane/butene ratio of 30:1), an excellent alkylate with a research octane number of approximately 99 was obtained, showing good industrial application prospects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".