Catalytic gasification of wheat straw in hot compressed (subcritical and supercritical) water for hydrogen production
Why this work is in the frame
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Bibliographic record
Abstract
Abstract To supplement the increasing energy demands and cope with the greenhouse gas emissions, biofuels generated from lignocellulosic biomass are gaining widespread attention. In this study, wheat straw was used as a candidate lignocellulosic biomass to produce hydrogen fuel through hydrothermal gasification. The fluid phases of water investigated for gasification included subcritical (300 and 370°C) and supercritical (450 and 550°C) phases. Along with the effects of temperature (300‐550°C), the influences of feed concentration (20‐35 wt%) and reaction time (40‐70 minutes) were comprehensively studied for wheat straw gasification in subcritical and supercritical water. To maximize hydrogen and total gas yields, the effects of two metal catalysts (eg, Ru/Al 2 O 3 and Ni/Si‐Al 2 O 3 ) were examined. Hydrogen and total gas yields, as well as lower heating values of the gas products, were comparatively evaluated during the subcritical and supercritical water gasification of wheat straw. Supercritical water gasification of wheat straw at 550°C with 20 wt% feed concentration for 60 minutes of reaction time resulted in higher yields of hydrogen (2.98 mmol/g) and total gases (10.6 mmol/g). When compared to noncatalytic gasification, catalytic gasification using 5 wt% loading of Ru/Al 2 O 3 and Ni/Si‐Al 2 O 3 enhanced the hydrogen yields up to 4.18 and 5.1 mmol/g, respectively, along with respective total gas yields of 15 and 18.2 mmol/g. Nonetheless, wheat straw‐derived biochar produced at high supercritical water temperatures also retained high carbon content and calorific value.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it