Biorefinery potential of <i>Eucalyptus grandis</i> to produce phenolic compounds and biogas
Bibliographic record
Abstract
Vanillin is widely known in the food industry as the main flavoring compound of vanilla. Its natural extraction from the seed is not enough to supply the worldwide vanillin demand; therefore, new chemical routes from biomass have been developed to satisfy the vanillin market. A biorefinery for forest waste valorization could be an opportunity to maximize the economic gains and reduce the environmental impact in an integrated approach. This work demonstrates the experimental production of vanillin and vanillic acid through black liquor oxidation, after alkaline pretreatment of Eucalyptus grandis W. Hill ex Maiden chips. Additionally, the remaining solid fraction was valorized by anaerobic digestion. The experimental yields in the oxidation stage were 4.37% and 2.14% (based on lignin) for vanillin and vanillic acid, respectively. The biogas productivity in anaerobic digestion was 163 mL·g volatile solids–1. These values were the basis for the process simulation to analyze the potential for an integrated biorefinery. From an economic perspective, the process is feasible at a minimal processing scale of 8.58 t·h–1. On the other hand, the environmental assessment concludes that the environmental impact is mainly affected by the CO2 and CH4 emissions from biogas upgrading.
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) | 0.000 | 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".