Pelagic <i>Sargassum</i> waste as an excellent feedstock for bioethanol production: hydrolysis optimisation and kinetics
Bibliographic record
Abstract
This study highlights the potential of marine macroalgae waste as a viable feedstock for bioethanol production. Compositional analyses have shown that this pelagic seaweed waste contains substantial carbohydrates. To further enhance the extraction of fermentable sugars from the biomass, a response surface methodology (RSM) statistical optimisation approach was applied, involving 27 experimental runs. Optimal hydrolysis conditions, determined through statistical analysis, consisted of a 0.8 M sulphuric acid concentration, a temperature of 130 °C, and a 60-min duration, resulting in a sugar yield of approximately 132 mg/g. The hydrolysis of Sargassum biomass followed a first-order reaction kinetics with an activation energy of 41.36 kJ/mol and a pre-exponential factor of 127 (molH2SO4)−1.s−1. Furthermore, the obtained hydrolysate was fermented using Saccharomyces cerevisiae NT116. This resulted in a maximum ethanol yield of 0.497 ± 1 g/g, highlighting the potential of this biomass in bioethanol production.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".