Sulphite addition during steam pretreatment enhanced both enzyme-mediated cellulose hydrolysis and ethanol production
Bibliographic record
Abstract
Sulphite addition during steam pretreatment of softwoods under acidic, neutral and alkaline conditions was assessed to try to minimize lignin condensation. Although pretreatment under neutral/alkaline conditions resulted in effective lignin sulphonation, non-uniform size reduction was observed. In contrast, acidic sulphite steam treatment at 210 °C for 10 min resulted in homogenous particle size reduction and water-insoluble component that was 62% carbohydrate and 33% lignin. This carbohydrate-rich substrate was readily hydrolyzed and fermented which indicated the lack of fermentation inhibitors in the steam-pretreated whole slurry. The use of high solid loading (25% w/v) resulted in a hydrolysis yield of 58% at an enzyme loading of 40 mg protein/g glucan and efficient fermentation (46.6 g/L of ethanol). This indicated that the addition of acidic sulphite at the steam pretreatment of softwoods improved both the enzymatic hydrolysis and fermentation of steam-pretreated whole slurries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".