Advances in Upgrading Process of Petroleum Residue: A Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Due to the depletion of light crude oil reserves, heavy crude oil and residues are the alternatives to meet ?the ?increasing global demand for light oil products. Heavy crude oil and residues are characterized by the presence of heavy ?hydrocarbon ?compounds which contain high levels of impurities such as metals, nitrogen, and sulfur-containing compounds. ?Methods of ?upgrading are required to increase refining efficiencies and to obtain high-quality products.? Upgrading processes can be categorized into three categories; ?carbon rejection processes, hydrogen addition processes, and a combination of the two. The catalyst can be used with any of these processes for better improvement. Many types of research have been carried out to develop a high-performance process which is stable, high commercial products yield, and low solids formation. In this work, recent advances on petroleum residues upgrading with catalyst, solvents, and thermal cracking were reviewed. Advantages and disadvantages of each process were discussed along with conditions and main features. Nanoparticles catalysts and supercritical fluids based-processes are the trends of upgrading due to the excellent performance of these processes.
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 it