Properties Analysis of Spent Catalyst for Fixed-Bed Residue Hydrotreating Unit: Composition of Deposited Elements Along Catalyst Bed
Bibliographic record
Abstract
Element compositions of spent catalyst from a commercial fixed-bed residue hydrotreating unit of Petro-China were analyzed in order to investigate the reasons for the catalyst deactivation. The spent catalysts were sampled from different axial position of the reactor. Depositions of C, H, S, N, Ni and V on the spent catalysts were studied. No necessary relation was observed for the contents of various deposited elements along the bed at the end of a run. The deposition amount of elements was mainly related to local reaction conditions and catalyst loading states in the fixed-bed. The catalysts with high metal depositions have low contents of coke, high contents of sulfur and high H/C, which indicates that residue hydrotreating is an autocatalytic process. Metal sulfides deposited on catalysts have a hydrogenation activity in residue hydrotreating. The coke on residue hydrotreating catalysts mainly comes from some specific condensed ring structures containing nitrogen existed in asphaltene which is difficult to hydrotreat. Key words: Spent catalyst; Residue hydrotreating; Deposited elements; Composition
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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".