Hydrogen-rich syngas production from sewage sludge and hydrochars via catalytic gasification with SrO
Bibliographic record
Abstract
This study investigates the production of high-quality syngas from sewage sludge and its hydrochars through gasification and catalytic gasification processes. The following types of sludge were analyzed: digested (MS1) and non-digested (MS2) municipal sludge from Silesian wastewater treatment plants (WWTPs) and two industrial sludge hydrochars (HC_IS1, HC_IS2). Hydrochars (HC_MS1, HC_MS2, HC_IS1, HC_IS2) were derived via hydrothermal carbonization at 200 °C and 2 h. Gasification and catalytic gasification processes with SrO were conducted under a CO 2 atmosphere at 850 °C. Gas chromatography was employed to identify syngas components, including H 2 , CH 4 , CO 2 , and CO. The results demonstrated that the presence of a catalyst significantly increased hydrogen (H 2 ) yield, particularly during the heating stage. For instance, hydrogen increased from 4 % to 21.7 % for HC_MS1, although with HC_MS2 no hydrogen was found until the addition of a catalyst, SrO, which increased hydrogen to 7.6 %. The findings confirm the potential of gasification for syngas production from sewage sludge and hydrochars. • Hydrochar is potential feedstock for hydrogen production via gasification. • H 2 -rich syngas is produced from sewage sludge and hydrochars via gasification. • Catalytic gasification with SrO in CO 2 atmosphere at 850 °C boosted H 2 yield. • Presence of SrO significantly increased H 2 yield.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".