Acidification of prehydrolysis liquor and spent liquor of neutral sulfite semichemical pulping process
Bibliographic record
Abstract
Acidification has been commercialized for producing kraft lignin from black liquor of kraft pulping process. This work intended to evaluate the effectiveness of acidification in extracting lignocelluloses from the spent liquor of neutral sulfite semichemical pulping (NSSC) process and from prehydrolysis liquor (PHL) of kraft-based dissolving pulp production process. The results showed that the NSSC and PHL spent liquors had some lignin-carbohydrate complexes (LCC), and that the square weighted counts of particles with a chord length of 50-150μm in the spent liquors were significantly increased as pH dropped to 1.5. Interestingly, the acidification reduced the lignosulfonate/lignin content of NSSC and PHL by 13% or 20%, while dropped their oligosugars content by 75% and 38%, respectively. On a dry basis, the precipitates had more carbon, hydrogen and a high heating value of 18-22MJ/kg, but less oxygen, than spent liquors. The precipitates of PHL could be used as fuel.
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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".