The liquefaction characteristics of poplar under <scp>CuMgAlOx</scp> catalysis in supercritical methanol
Bibliographic record
Abstract
Abstract In an effort to explore the potential energy of biomass and reduce industrial reliance on fossil fuels, this study investigates the liquefaction of poplar wood using supercritical methanol and a CuMgAlOx catalyst. It assesses the composition of liquefied products and performs a comprehensive life‐cycle assessment. Results display that at 360°C, with 1 h of CuMgAlOx, poplar wood's conversion rate reached 98.4%. The proportion of alcoholic compounds in the liquefaction products increased dramatically from 7.99% without a catalyst to 70.81% with it, a rise of 786.23%. Moreover, the process's global warming potential (GWP) intensity is significantly lower at 0.886 gCO2eq/MJ compared to the 93 gCO2eq/MJ from conventional petroleum refining, underscoring its substantial emission reduction potential.
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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) | 0.000 | 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".