Tungsten effect over co-hydrotalcite catalysts to produce hydrogen from bio-ethanol
Bibliographic record
Abstract
A great stabilization effect of tungsten over the Co-hydrotalcite catalysts to produce H2 from ethanol in steam reforming was found. The catalysts were characterized by N2 physisorption (BET area), X-ray diffraction, Infrared ,Raman and UV-vis spectroscopies. Catalytic evaluations were performed in a fixed bed reactor using a water/ethanol mol ratio of 4, at 450°C, and the W concentration stud- ied was from 0.5 to 3 wt%. As W concentration increases, the intensity of crystalline reflections of the Co-hydrotalcite catalysts decreases. There were found porous with the shape of parallel layers with a monomodal mesoporous distribution. Superficial chemical groups as: -OH, H2O, Al-OH, Mg-OH, W-O-W and CO32- were found by infrared spectroscopy. Catalyst with low amounts of W (1%) showed both, the highest H2 production and the best catalytic stability. The smallest pore volume of this catalyst could be related with long residence times of ethanol in the pores. Tungsten promoted the conversion for the Co-hydrotalcite catalysts. The reaction products were: H2, CO2, CH3CHO, CH4 and C2H4 and the catalysts did not produce CO.
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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".