Syngas Quality Enhancement by CO<sub>2</sub> Injection during the Co-Gasification of Biomass and Plastic
Bibliographic record
Abstract
Gasification technologies have been considered to be viable waste enhancement avenues for diverting mixed nonrecycled plastic-containing waste from landfills. The main objective of this work was to investigate CO 2 utilization with the air gasification of mixed plastics and biomass. High-density polyethylene (HDPE) was co-gasified with Douglas fir, air, and CO 2 in a semibatch updraft gasifier with supporting thermogravimetric analyzer (TGA) testing. Possible reaction mechanisms of the mixed feedstock with CO 2 injections were discussed by comparing the gas, tar, and char products of the gasifier with the TGA data. Injecting 10 and 20 vol % CO 2 in air gasification with an air to fuel ratio of 0.3 improved carbon conversion from the tar to the gas phase by 28 and 43 carbon weight %, respectively. CO 2 addition was an effective moderator of the H 2 /CO ratio, beneficial to tar reduction and enhanced the energy density of the syngas, improving the tunability of the gasification process.
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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".