Recent advances in bioethanol production from lignocelluloses: a comprehensive review with a focus on enzyme engineering and designer biocatalysts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many countries have their biofuel policy programs in place as part of their overall strategy to achieve sustainable development. Among biofuels, bioethanol as a promising alternative to gasoline is of substantial interest. However, there is limited availability of a sufficient quantity of bioethanol to meet demands due to bottlenecks in the present technologies to convert non-edible feedstocks, including lignocelluloses. This review article presents and critically discusses the recent advances in the pretreatment of lignocellulosic biomass, with a focus on the use of green solvents, including ionic liquids and deep eutectic solvents, followed by enzymatic saccharification using auxiliary proteins for the efficient saccharification of pretreated biomass. Different techniques used in strain improvement strategies to develop hyper-producing deregulated lignocellulolytic strains are also compared and discussed. The advanced techniques employed for fermentation of mixed sugars contained in lignocellulosic hydrolysates for maximizing bioethanol production are summarized with an emphasis on pathway and transporters engineering for xylose assimilation. Further, the integration of different steps is suggested and discussed for efficient biomass utilization and improved ethanol yields and productivity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 it