Effects of Ultrasound Treatment on the Upgradation of Heavy Gas Oil
Bibliographic record
Abstract
Catalytic hydrotreating is the most effective process for upgrading heavy gas oil. However, the operating conditions such as high temperatures (633−673 K), high pressures (8.6−8.9 MPa), and consumption of large amounts of catalyst and hydrogen place constraints and limitations on the process. In this investigation the ultrasonic energy is used to treat the heavy gas oil (HGO) without the use of any additives at atmospheric pressure. The lighter gas hydrocarbons given off during the ultrasonic treatment of HGO were identified as methane, ethylene, ethane, and propylene. The basic nitrogen-containing compounds in HGO were more easily cleaved by cavitational energy than that of nonbasic compound. A maximum nitrogen and sulfur conversion of 11% and 7%, respectively, and a 5% reduction in the viscosity were obtained at the optimized sonochemical conditions. A radical chain mechanism is proposed to demonstrate the reactions of hydrocarbons initiated by ultrasound.
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 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) | 0.000 | 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 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".