Catalytic Steam Reforming of Aqueous Phase of Bio-Oil over Ni-Based Alumina-Supported Catalysts
Bibliographic record
Abstract
Production of hydrogen (H 2 ) from catalytic steam reforming of the aqueous phase of bio-oil was investigated in a fixed bed tubular flow reactor over nickel-based alumina-supported catalysts promoted with magnesia (Ni-MgO/Al 2 O 3 ). The effects of time, amount of Ni, preparation condition, and initial bio-oil to water ratio on the yield of various outlet gases including hydrogen was investigated at 850 °C, and the outlet gas distributions were obtained. The average H 2 yield was very low with a maximum of 30% over the alumina support when the aqueous phase of the bio-oil at a bio-oil to water ratio of 1 was employed. The hydrogen yield nearly doubled with the addition of 12.8% nickel and 33.3% magnesia for the three bio-oil aqueous phase samples at various bio-oil to water ratios. This effect was more pronounced in the aqueous bio-oil phases with greater water content. On the contrary, the effect of the preparation method on H 2 yield was more pronounced in the aqueous phase samples with lower water content. Among the catalysts tested, the highest H 2 yield (61%) was achieved over Ni-MgO/Al 2 O 3 -3 with the aqueous phase of bio-oil with a bio-oil to water ratio of 1/1, indicating that a greater bio-oil to water ratio does not necessarily provide greater H 2 yield.
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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".