Hydrogen Production from Supercritical Water Gasification of Model Compounds of Crude Glycerol from Biodiesel Industries
Bibliographic record
Abstract
Biodiesel production through transesterification results in a large quantity of crude glycerol as a byproduct, the utilization of which is technically and economically challenging. Because of the ability to efficiently process wet feedstocks, supercritical water gasification (SCWG) is utilized in this study to convert crude glycerol into hydrogen-rich syngas. A significant challenge addressed through this study is the decomposition routes of different heterogeneous components of crude glycerol during SCWG. Pure glycerol, methanol and oleic acid were investigated for SCWG as the model compounds of crude glycerol. SCWG of model compounds at temperature, pressure, feedstock concentration and reaction time of 500 °C, 23–25 MPa, 10 wt% and 1 h, respectively, revealed methanol to exhibit the highest H2 yield of 7.7 mmol/g, followed by pure glycerol (4.4 mmol/g) and oleic acid (1.1 mmol/g). The effects of feedstock concentration from 30 wt% to 10 wt% increased H2 yield from all model compounds. Response surface methodology (RSM) was used to develop a response curve to visualize the interactive behavior and develop model equations for the prediction of H2-rich gas yields as a function of the composition of model compounds in the crude glycerol mixture. Predictive models showed a good agreement with experimental results, demonstrating high accuracy and robustness of the model. These findings demonstrated a strong potential of crude glycerol for SCWG to generate H2-rich syngas.
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".