Experimental studies on the effect of ultrasonic treatment and hydrogen donors on residual oil characteristics
Bibliographic record
Abstract
Residual oil, the residue after the distillation of crude oil, imposes deleterious effects on refinery due to its high viscosity and asphaltene content. In this context, ultrasonic technology has been widely applied in refining processes given its high efficiency and minimal environmental impacts. To guide the selection of operation parameters, in this work, we probed the effect of treatment duration, power, and hydrogen donor on the characteristics of residual oil under ultrasonic treatments. Underlying mechanisms of ultrasonic treatments, in the absence and presence of hydrogen donors, were verified through systematically analyzing viscosity, component conversion, molecular weight, hydrogen distribution, and functional groups of residual oil. While viscosity reductions under low-power density treatment are caused by colloidal system disaggregation, high-power density treatment can bring in both chemical bond cleavage and colloidal system disaggregation. In addition, adding hydrogen donor can effectively prevent radical recombination, and thus increases the yield of saturate. These results provide fundamental understandings on the effects of ultrasonic treatments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".