Valorizing Waste Lignocellulose-Based Furniture Boards by Phosphoric Acid and Hydrogen Peroxide (Php) Pretreatment for Bioethanol Production and High-Value Lignin Recovery
Bibliographic record
Abstract
Three typical waste furniture boards (fiberboard, chipboard, and blockboard) were pretreated with phosphoric acid and hydrogen peroxide (PHP). The fractionation process of these feedstocks was attempted in order to harvest the cellulose-rich fraction for enzymatic hydrolysis and bioethanol conversion; further, lignin recovery was also considered in this process. The results indicated that 78.9–91.2% of the cellulose was recovered in the cellulose-rich fraction. The decreased crystallinity, which promoted the water retention capacity and enzyme accessibility, contributed greatly to the excellent hydrolysis performance of the cellulose-rich fraction. Therefore, rather high cellulose–glucose conversions of 83.3–98.0% were achieved by hydrolyzing the pretreated furniture boards, which allowed for harvesting 208–241 g of glucose from 1.0 kg of feedstocks. Correspondingly, 8.1–10.4 g/L of ethanol were obtained after 120 h of simultaneous saccharification and fermentation. The harvested lignin exhibited abundant carboxyl –OH groups (0.61–0.67 mmol g−1). In addition, approximately 15–26 g of harvested oligosaccharides were integrated during PHP pretreatment. It was shown that PHP pretreatment is feasible for these highly recalcitrant biomass board materials, which can diversify the bioproducts used in the integrated biorefinery concept.
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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) | 0.001 | 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 | 0.000 |
| 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 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".