An integrated process for removing the inhibitors of the prehydrolysis liquor of kraft‐based dissolving pulp process via cationic polymer treatment
Bibliographic record
Abstract
The prehydrolysis liquor (PHL) of the kraft-based dissolving pulp production process contains various amounts of hemicelluloses that can be utilized in the production of value-added products. In this work, a new process was proposed for removing the inhibitors of PHL via employing a flocculation concept to facilitate the utilization of hemicelluloses. Lignin, lignocelluloses/cationic polymer complexes, and possibly ethanol are the main products of this process. This process has been experimentally evaluated with an industrially produced PHL and cationic polymers. The results showed that 16% of lignin, 19% of acetic acid, 43% of furfural, and insignificant amount of sugars were removed from PHL via pretreating PHL with acid and lime at pH 7. Furthermore, by adding 0.4-0.5 mg g(-1) polydiallyldimethylammonium chloride (PDADMAC) or chitosan to the pretreated PHL, 12-14% acetic acid, 40-50% furfural, 5-6% monomeric sugars, and 25% oligomeric sugars were removed from the PHL. The complexes made from these components may be applied as organic fillers in various industries. Alternatively, by adding 1.2 or 1.4 mg g(-1) PDADMAC or chitosan to the pretreated PHL, 30 or 35% of lignin was removed, respectively, which induced complexes that could be used as a fuel source. The composition of the complexes formed was also determined in this work.
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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".