Thermodynamic Analysis of Autothermal Reforming of Synthetic Crude Glycerol (SCG) for Hydrogen Production
Bibliographic record
Abstract
This study presents the thermodynamic modelling of hydrogen production from autothermal reforming of synthetic crude glycerol using the Peng-Robinson Stryjek-Vera thermodynamic model and Gibbs free energy minimization approach. In order to simulate the typical crude glycerol, a solution was prepared by mixing glycerol, methanol, soap, and fatty acids. The equilibrium compositions of the reforming gas were obtained and the impacts of the operating temperature, steam to crude glycerol ratio (S/SCG), and oxygen to crude glycerol ratio (O/SCG) on hydrogen production were investigated. Under isothermal conditions, the result showed that maximum hydrogen production is favoured at conditions of high temperatures, high S/SCG, and low O/SCG ratio. However, under thermoneutral conditions where no external heat is supplied to the reformer, results indicate that high hydrogen yield is realised at conditions of high temperatures, high S/SCG and high O/SCG ratio. Furthermore, it was concluded that under thermoneutral condition, steam to SCG ratio of 3.6, oxygen to SCG ratio of 0.75, and adiabatic temperature of 927 K yields maximum hydrogen.
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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".