Mass Transfer during Pressurized Low-Polarity Water Extraction of Phenolics and Carbohydrates from Flax Shives
Bibliographic record
Abstract
The effects of pH-buffered water and NaOH solution on pressurized low-polarity water (PLPW) extraction were investigated to determine the optimal conditions for the extraction of lignocellulosic components from flax shives. A high NaOH concentration (0.1 M) and a high pH of buffered water (pH 13) increased the rates of extraction by increasing values of the effective diffusion coefficient ( D e ) from 9.1 × 10 -11 m 2 /s to 1.5 × 10 -10 m 2 /s during PLPW extraction of free phenolic compounds. The concentration of NaOH exerted a significant effect on extraction of free phenolic compounds, whereas PLPW extraction of total carbohydrates was not significantly affected by variation of the pH and NaOH concentration. The maximum concentrations of free phenolic compounds (5.7 g/kg of dry flax shive (DFS)) and total carbohydrates (260 g/kg of DFS) were obtained using 0.1 M NaOH solution and water, respectively, at 230 °C and a flow rate of 2 mL/min. To determine the mechanism that controlled the PLPW extraction of free phenolic compounds and total carbohydrates, the extraction kinetics were studied using a two-site kinetic model and a thermodynamic model. The curves generated using these two models showed good fits to the experimental data within the tested range of flow rate, demonstrating that the extraction mechanism is controlled by both internal diffusion and external elusion. The kinetic values, including the fraction of the analyte released ( F ) and the kinetic constants obtained from the two-site kinetic model ( k 1 and k 2 ), increased as the flow rate increased, indicating that the internal diffusion step is not totally independent of the flow rate, because the internal diffusion can be increased by the higher external concentration gradient that is caused by the higher flow rate.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".