Production of bio‐polyurethane (<scp>BPU</scp>) foams from greenhouse/agricultural wastes, and their biodegradability
Bibliographic record
Abstract
Abstract The exploration of effective utilization of greenhouse wastes is challenging. This paper demonstrates a hydrothermal treatment approach involving the co‐liquefaction of greenhouse wastes with agricultural residue in a mixed solvent of water and ethanol in the presence of a base catalyst, to convert greenhouse wastes and corn stalk into bio‐oil/bio‐polyol at a very high yield of 57.2%, accompanied by a very low yield of solid residue. This bio‐oil (hydroxyl number: 305 mg KOH/g) was successfully used as bio‐polyol to substitute up to 50% petroleum‐based polyol for the preparation of bio‐polyurethane (BPU) foams. The biodegradability of the BPU foams was also studied by incubation with Dyella sp. for a period of 8 weeks. The weight loss, Fourier‐transform infrared (FTIR) spectra, thermogravimetric analysis (TGA) results, and scanning electron microscopy (SEM) images of foam samples were collected and analyzed. The BPU foams exhibited much better biodegradability than the petroleum‐based polyurethane (PU) foam. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".