Using Biomass Gasification Mineral Residue as Catalyst to Produce Light Olefins from CO, CO<sub>2</sub>, and H<sub>2</sub> Mixtures
Bibliographic record
Abstract
Abstract Gasification is a process to transform solids, such as agricultural and municipal waste, into gaseous feedstock for making transportation fuels. The so‐called coarse solid residue (CSR) that remains after this conversion process is currently discarded as a process solid residue. In the context of transitioning from a linear to a circular society, the feasibility of using the solid process residue from waste gasification as a solid catalyst for light olefin production from CO, CO2, and H2 mixtures was investigated. This CSR‐derived catalyst converted biomass‐derived syngas, a H2‐poor mixture of CO, CO2, H2, and N2, into methane (57 %) and C2–C4 olefins (43 %) at 450 °C and 20 bar. The main active ingredient of CSR was Fe, and it was discovered with operando X‐ray diffraction that metallic Fe, present after pre‐reduction in H2, transformed into an Fe carbide phase under reaction conditions. The increased formation of Fe carbides correlated with an increase in CO conversion and olefin selectivity. The presence of alkali elements, such as Na and K, in CSR‐derived catalyst increased olefin production as well.
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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".