Extraction and Separation of Carbohydrates and Phenolic Compounds in Flax Shives with pH-Controlled Pressurized Low Polarity Water
Bibliographic record
Abstract
A bench-scale pressurized low polarity water (PLPW) extractor was used for the extraction and separation of hemicellulose, cellulose, lignin, and other phenolic compounds in flax shives. In the first part of this research, the key PLPW extraction process variables of temperature, pH, and flow rate, were optimized using central composite design (CCD). Temperature and pH of water had a significant affect on the fractionation of carbohydrates (cellulose and hemicellulose), lignin, and other phenolics. The optimal extraction conditions for the separation of hemicellulose and lignin, determined by the optimization using CCD, were 170 degrees C, pH 3.0, and a flow rate of 2.5 mL/min. Under these extraction conditions, 39.3% of the initial biomass or feed, 70.1% of the hemicellulose, 35.3% of the lignin, and 5.3% of the cellulose were extracted from the flax shives. In order to improve the purity and yield of the cellulose, a two-stage PLPW extraction was examined. The first stage was designed to remove hemicellulose by water at 170 degrees C and the second stage was intended for delignification by a pH 12 buffer at 220 degrees C. The two-stage PLPW extraction effectively removed 63.2% of the feed, 97.3% of hemicellulose, and 86.3% of lignin, while solubilizing 23.9% of cellulose; resulting in a solid residue containing 0.7 g of hemicellulose, 3.5 g of lignin, and 27.3 g of cellulose/100 g of DFS. The PLPW extraction is able to extract and separate components in flax shives by changing pH and temperature. The best case occurs between pH 9.5 and 12, resulting in maximum solubilization of hemicellulose and lignin.
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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".