Enzyme Recycling by Adsorption during Hydrolysis of Oxygen-Delignified Wheat Straw
Bibliographic record
Abstract
Enzyme recycling by adsorption from supernatant to fresh substrate is a promising strategy to reduce enzyme expenses and the production cost of lignocellulosic ethanol. The study was performed using oxygen-delignified wheat straw, and the effect of lignin content, enzyme loading, and hydrolysis time on recycling was determined. The percent of recycled cellulases, 0–35% of initial cellulase loading, increased with increasing enzyme loading and hydrolysis time but decreased with increasing lignin content. Cellulose conversions of 10–71% were achieved during the second hydrolysis round using only recycled cellulases indicating the existence of a highly active subset of enzymes. To achieve constant production of sugars during enzyme recycling, fresh cellulases were loaded before the second hydrolysis round to match the cellulase loading used in the first round. Subsequently, similar glucose, xylose, and protein concentrations were obtained at the end of the first and second rounds for all conditions. Recycling mass balances were developed to support future techno-economic analyses to determine the impact of enzyme recycling on the cost of ethanol.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".