Recycle of Vanadium and Nickel-Based Catalysts in a Hydroconversion Process
Bibliographic record
Abstract
Vanadium and nickel-based carbonaceous solids derived from the controlled burning of coke/bottoms/resid have the potential to serve as attractive catalysts in slurry-based upgrading processes. Carbonaceous solids comprised of a high concentration of metals, namely, Venturi fines (solids obtained from an ExxonMobil flexicoker unit and containing ∼12 wt % total metals) and flexicoker ash (prepared from the mild burning of Venturi fines and gasifier bed coke and containing ∼50 wt % total metals) were more effective slurry catalysts than those comprised of less than 5 wt % total metals. Analyses of the hydroconverted products produced from slurry hydroprocessing autoclave experiments indicated that at 8 wt % solids in the feed sulfided Venturi and flexicoker carbonaceous catalysts were comparable on a once-through and recycle basis. However, on the basis of catalyst performance versus total metals dispersed in the feed, Venturi fines were superior to flexicoker solids. X-ray diffraction analysis of the source flexicoker solids suggest that the primary metal species was vanadium pentoxide. If treated with elemental sulfur/H 2 (g) at elevated temperature and pressure the oxide formed active metal sulfide catalysts. Possible reaction pathways for the in situ formation of the metal sulfides are proposed. Upon recycling, carbonaceous catalyst solids were less effective in producing hydroconversion products of similar quality to those achieved on a once through basis. Carbonaceous material deposited on the catalysts during the hydroconversion process were removed via mild calcining to regenerate the solids and experimental data clearly indicated that the catalyst activity of the calcined solids was not restored to that exhibited by fresh sulfided solids. A reduction in surface area of the solids upon calcining was observed and is suggested to contribute to catalyst deactivation.
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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 | 0.000 | 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) | 0.001 | 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".