Evaluation of the Physical-Chemical Properties in Petroleum Coke
Bibliographic record
Abstract
In this paper, commercial petroleum cokes were analyzed, before and after heat treatment in order to evaluate the physical-chemical properties. The content of moisture, volatile matter, sulphur, ash and metals (Fe Ni, Cr) was determined. The results showed that temperature increasing led to the removal of volatile matter and sulphur content; higher separation of sulphur was observed for coke obtained from atmospheric residue and from decanted oil. The ash content indicates the presence of inorganic admixtures in coke. Metal concentrations increased through calcining, due to the weight loss from removal of the volatile matter; the coke samples revealed the higher content of nickel (151 to 279 ppm) which is the most represented metal component in the coking feedstock. Physical-chemical parameters indicate that the analyzed cokes can be used in anode –grade production. Key words: Anode materials; Petroleum coke; Moisture; Sulphur; Volatile matter; Metals
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".