Co‐liquefaction of lignite and biomass over Ni<sub>7</sub>W<sub>3</sub> and Ni<sub>3</sub>W<sub>7</sub> catalysts
Bibliographic record
Abstract
Co‐liquefaction of lignite and biomass was carried out in an autoclave by varying the biomass type and initial hydrogen pressure as well as the catalyst. The properties of the catalysts, raw materials, and residues were characterized by Ultimate analyses, BET, H2‐TPR, TG/DTG, and TPO. The results showed that synergetic effect between lignite and biomass (pine shoot, corn cob, and corn stalk) might be positive, insignificant, or even negative depending on biomass type and reaction conditions. Higher hydrogenation pressure favours the formation of oil and reduction of asphaltene. Catalysts also play important roles in the performance of co‐hydrogenation of lignite and biomass. Highly active catalysts (Ni3W7) may form more active hydrogen species in the solution, stabilizing smaller fragments and increasing the formation of oil.
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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) | 0.001 | 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".