Development of a novel autothermal reforming process and its economics for clean hydrogen production
Bibliographic record
Abstract
Abstract A novel autothermal reforming process, basically a circulating fluidized‐bed membrane reformer (CFBMR) with continuous catalyst regeneration and gas–solid separation, is developed. Direct contact between cold feeds and hot circulating catalyst is found to be the best configuration. Using statistical correlations and cost factors, hydrogen economics is evaluated. Hydrogen production cost decreases as the plant size increases. For a 100 kg‐H2/day plant, the costs are $2.05 and $2.22/kg‐H2 for methane and heptane feeds, respectively. This is lower than the literature values of $9.10/kg‐H2 by steam methane reforming based on the present generation of fixed‐bed reformers. For typical 214 ton‐H2/day industrial plants, the costs using our novel CFBMR are $0.50 and $0.66/kg‐H2 for methane and heptane feeds, respectively, which is lower than the industrial cost of $0.74–0.97/kg‐H2 for steam methane reforming using the fixed‐bed configuration. The sensitivity analysis of the effect of the price of hydrocarbons on the hydrogen production cost shows that the cost of hydrocarbons affects the hydrogen economics significantly. Cost comparison shows that this novel ACFBMR can be a more efficient and more economical pure hydrogen producer. Copyright © 2006 Curtin University of Technology and John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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".