Beneficiation of renewable industrial wastes from paper and pulp processing
Bibliographic record
Abstract
Black liquor (spent cooking liquor) is one of the major byproducts of pulp and paper manufacturing. Black liquor contains 10–50% lignin, which is the main organic matter found within that liquor. Different types of black liquors are obtained as per the type of feedstock, pulping process and cooking method adopted by industries. In recent years, industries have been required to accommodate newer varieties of feedstock such as non-wood and recycled fibers during the delignification process, which can save plenty of trees and hence reduce their carbon footprint. Therefore, the newer black liquors being generated differ in their physical characteristics, chemical composition, and energy content from that of traditional processes.<br />Currently, black liquor is seen as a platform for the production of many renewable materials for industrial applications that can be environmentally friendly with the potential to be used substitute for fuel and commercial materials. However, most of the published review articles focus on the kraft spent liquor and its derived kraft lignin that is obtained from kraft pulping process at the pulp and paper as a source of bio-fuel and biomaterials. Meanwhile, several other black liquors such as soda, and neutral sulfite spent (NSSC) liquor and their derived lignin are not highlighted as sources of biofuel and biomaterials. Therefore, this review highlights all the types of black liquors including soda, and neutral sulfite spent (NSSC) liquor in terms of their sources, physical and chemical characterization, purification processes, and the potential applications of black liquor and its derived lignin.
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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".