Characteristic Research on CaO Sorption Enhanced Biomass Directional Entrained-Flow Gasification
Bibliographic record
Abstract
As the only renewable energy which can be converted into liquid fuels, biomass has developed various technologies of energy utilization. In order to adjust the syngas composition, increase the ratio of H2/CO and reduce CO2 content, this paper conducted biomass gasification experiment in an entrained flow bed on CaO sorption. The paper studied influence factors like the gasification temperature, ratio of CaO/B and gasification parameters, such as ratio of H2/CO, cold gas efficiency, cold gas yield or tar content in syngas. The result showed that raising gasification temperature or increasing added content of CaO which were beneficial to the improvement of H2 content. A maximum H2 output with a concentration of 62.7% and H2/CO ratio of 3.19 was achieved at CaO/C=1, H2O/B=0.3 and T=1100°C, meanwhile the cold gas efficiency was 86.07%, the cold gas yield reached 1.2Nm3/kg biomass, and the tar content was dropped to 314.6mg/Nm3.
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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".