Forest Biomass and Paper Industry, a Pathway to Green Biofuels
Bibliographic record
Abstract
The components of wood, celluloses, hemicelluloses and lignin, can be separated and converted into new non paper products.This paper treats the specific case of lignin and hemicellulose extraction from a Kraft pulping process.Two processes have been investigated for the extraction of lignin from black liquor.One is an enhanced version of precipitation of lignin under low pH conditions achieved by carbonation of Kraft black liquor.The second process focuses on the acidification of the black liquor by electrodialysis with a bipolar membrane.This process produces clean lignin and valuable caustic soda.The extraction of hemicelluloses from wood chips and their partitioning into a mixture of C5 and C6 sugars can be accomplished by a two-step hydrolysis.The sugars can then be converted into a large number of derivatives.The case of fermentation into butanol is presented.The energy intensification of the site eliminates the requirement for fossil fuel thus enhancing the feasibility of the green integrated forest biorefinery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".