Sugar Recovery and Fermentability of Hemicellulose Hydrolysates from Steam-Exploded Softwoods Containing Bark
Bibliographic record
Abstract
The hemicellulose sugar recovery and ethanol production obtained from SO2-catalyzed steam explosion of a mixed white fir (70%) and ponderosa pine (30%) feedstock containing bark (9% dry weight/dry weight) was assessed. More than 90% of the available hemicellulose sugars could be recovered in the hydrolysate obtained after steam explosion at 195 degrees C, 2.38 min, and 3.91% SO2, with 59% of the original hemicellulose sugars detected in a monomeric form. Despite this high sugar recovery, this hydrolysate showed low ethanol yield (64% of theoretical yield) when fermented with a spent sulfite liquor-adapted strain of Saccharomyces cerevisiae. In contrast, most hydrolysates prepared at higher steam explosion severity showed comparable or higher ethanol yields. Furthermore, the hydrolysates prepared from bark-free feedstock showed better fermentability (87% of theoretical yield) despite containing higher concentration of known inhibitors. The ethanol yield from the hydrolysate prepared from a bark-containing wood sample could be improved to 81% by an extra stage acid hydrolysis (121 degrees C for 1 h in 3% sulfuric acid). This extra stage acid hydrolysis and steam explosion at higher severity conditions seem to improve the fermentability of the hydrolysates by transforming certain inhibitory compounds present in the hydrolysates prepared from the bark-containing feedstock and thus lowering their inhibitory effect on the yeast used for the ethanol fermentation.
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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) | 0.001 | 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".