Removal of linear and monobranched alkane from aviation gasoline by 5A zeolite adsorption for octane number enhancement
Bibliographic record
Abstract
Abstract Due to continued concern about effects of tetraethyl lead (TEL) emission on the environment and human health, the complete removal of TEL from aviation gasoline (avgas) is a desirable pursuit. In order to maintain high antiknock performance of avgas, an advanced adsorption method was developed using 5A zeolite to remove linear and monobranched alkane from avgas for octane number enhancement. An experimental study of single, binary, and quaternary adsorption of octane isomers on a fixed bed reactor was performed in this work. The effects of partial pressure, operating temperature, and initial mixture composition on breakthrough curves and sorption selectivity were thoroughly studied. At fixed partial pressure, normal octane was the strongest‐adsorbed component, followed by 2‐methylheptane, 2, 5‐dimethylhexane, and 2, 2, 4‐trimethylpentane. Adsorption capacity of all components increased with increased partial pressure and decreased with increased operating temperature. However, for all binary mixtures studied in this work, the sorption selectivity decreased as total pressure increased. At equimolar concentrations the normal and monobranched isomers were preferentially adsorbed, while when the volume percentages of the isomers were different, the adsorption of the isomer with the higher volume ratio was favoured. The quaternary breakthrough curves for octane isomers at 473 K with each component having partial pressure of 0.15 kPa also indicated the feasibility of simultaneous removal of normal and monobranched isomers from a multiple‐component mixture by this 5A zeolite.
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) | 0.000 | 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) | 0.001 | 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".