Optimizing the separation of xylose/xylan from eucalyptus woodchips in the autohydrolysis process
Bibliographic record
Abstract
Abstract Effective separation of various components in biomass is critical for biorefinery. Autohydrolysis is a commercialized unit operation to remove hemicelluloses, such as xylan, in producing high‐quality cellulose (the so‐called dissolving pulp) in the pre‐hydrolysis kraft process. In the present study, the autohydrolysis of eucalyptus woodchips was investigated for the purpose of producing dissolving pulps, with a focus on the production of cellulose acetate grade dissolving pulp. First, the effects of liquid‐to‐solid ratio, maximum temperature, and time on hemicelluloses removal were comprehensively studied, and the total xylose saccharides concentration and total xylose saccharides yield were determined as a function of the P factor and log( R o ). The three‐variable Box–Behnken design of the response surface methodology was followed to optimize the autohydrolysis conditions, aiming to achieving the maximum removal of xylan. The as‐obtained optimal conditions were: liquid‐to‐solid ratio of 5.5 mL · g −1 , maximum temperature of 165°C, and time of 120 min, with its P factor of 867 h and log( R o ) of 4.03. Under these conditions, the total xylose saccharides concentration was 16.43 g · L −1 . Furthermore, the autohydrolysis yield was investigated. The results showed that the purity of as‐prepared cellulose substrate as a result of autohydrolysis at a P factor of 867 h (log( R o ) of 4.03) can meet the stringent requirement of cellulose acetate grade dissolving pulp. Furthermore, the pre‐hydrolysis liquor compositions were compared between the typical autohydrolysis conditions for rayon grade dissolving pulp (a P factor of 690 h and log( R o ) of 3.91) and the optimal conditions (a P factor of 867 h and log( R o ) of 4.03).
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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) | 0.000 | 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".