Chemical-Looping Gasification of Biomass for Hydrogen-Enriched Gas Production with In-Process Carbon Dioxide Capture
Bibliographic record
Abstract
The research presents an innovative idea of developing a continuous H 2 production process employing fluidized-bed technology from agricultural biomass with in situ CO 2 capture and sorbent regeneration. Novelty of the process lies in the generation of relatively pure H 2 from biomass with CO 2 as a byproduct using steam as the gasifying agent. Another unique feature of the process is internal regeneration of the sorbent, fouled in the gasifier. Thus, the technology will serve the twin purpose of regenerating the sorbent and generation of N 2 -free H 2 and CO 2 . This work reports theoretical energy analysis and experimental investigation of the process. The system efficiency of the chemical-looping gasification process at an ideal scenario is found to be 87.49% with biomass as fuel. A sensitivity analysis for system efficiency is also conducted by varying carbon-capture and regeneration efficiencies. The experiments conducted in a batch-type fluidized-bed steam gasifier using CaO as the sorbent shows a 71% concentration of H 2 and nearly 0% concentration of CO 2 in the product gas when sawdust was used as the feedstock. In a separate test using a circulating fluidized-bed reactor as the regenerator, a 40% regeneration of CaO is also achieved at a calcination temperature of 800 °C.
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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".