Enrichment of Second Generation Ethanol Concentration Obtained from Napier Grass Pretreated with Sulfuric Acid and Hydrothermal Pretreatment
Bibliographic record
Abstract
Enhancing sugar concentration is crucial for improving ethanol yield in biorefinery processes, enabling more efficient downstream recovery. This study investigates the hydrothermal pretreatment of Napier grass with 2% sulfuric acid to boost sugar recovery and ethanol production by incorporating a concentration step. After pretreatment, the liquid fractions were concentrated two-fold and four-fold through rotary evaporation and freeze-drying, resulting in a significant increase in sugar levels, with a 3.5-fold rise in sugar concentration achieved through rotary evaporation compared to unconcentrated samples. However, ethanol production was limited by elevated levels of inhibitors, such as acetic acid and furfural. The maximum ethanol concentration reached was 2.43%, from a liquid fraction concentrated four-fold. These results highlight the necessity of concentration techniques to improve sugar recovery, while also emphasizing the importance of removing inhibitors to increase ethanol yields and enhance the overall efficiency of biorefining processes.
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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) | 0.001 | 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".