Novel Catalyst for Cracking of Biomass Tar
Bibliographic record
Abstract
Cracking of biomass tar was investigated over Ni/dolomite catalyst prepared by the incipient wetness method using modified dolomite as precursor. Modified dolomite was prepared by mixing Fe 2 O 3 powders with natural dolomite powders to increase Fe 2 O 3 content for higher activity of tar cracking. Four other catalysts (natural dolomite, modified dolomite, ICI-46-1, and Z409) were tested and compared with Ni/dolomite catalyst. The effects of temperature, steam-to-carbon, and space velocity on tar conversion were explored. Ni/dolomite is shown to be very active and useful for tar removal. A 97% tar removal is easily obtained at catalyst temperature of 750 °C and space velocities of 12 000 h - 1 . The minimum S / C ratio for Ni/dolomite was 2.5 at a catalyst temperature of 750 °C to prevent the formation of the coke on the catalyst. No obvious deactivation of catalyst was observed in 60 h on-stream tests. Compared with the Ni-based catalysts (ICI-46-1, Z409), Ni/dolomite catalyst is cheap and has also excellent activity and anticoke ability.
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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".