From biomass-rich residues into fuels and green chemicals via gasification and catalytic synthesis
Bibliographic record
Abstract
Recycling carbon present in residual streams enhances sustainability and creates local wealth.Enerkem Inc. is a leading biomass gasification company headquartered in Montreal, Québec.The approach Enerkem has been developing involves: identification of low cost residual streams as feedstock, sorting, biotreatment (anaerobic and/or aerobic) and preparation of an ultimate residue (RDF).The latter is a rather uniform material that can be fed, as a fluff, to a bubbling bed gasifier in a staged gasification to carry out, sequentially, the needed chemical reactions that result in high syngas yields.Process can be adjusted to reach desired gas composition for synthesis or electricity generation as well as gas conditioning to produce an ultraclean syngas.Products for such a process are: i) syngas with an appropriate range of H 2 /CO ratios, ii) CO 2 (which is recovered), iii) solid char as a residue composed of the inorganic fraction of the raw material and some unconverted carbon that "coats" the inorganic matrices, and iv) water that needs to be treated to meet the sewage specifications and thus be sent into the water distribution system of a given municipality.Enerkem is developing two parallel valorisation routes; a) heat and power and b) synthesis of (bio)methanol as a high yield product.The methanol is the platform intermediate that can be turned into ethanol (also with high yields), and other green chemicals.Yields of ethanol as the end product are above 350Energy and Sustainability III 123 www.witpress.com,
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".