Synthesis of a Renewable, Waste‐Derived Nonisocyanate Polyurethane from Fish Processing Discards and Cashew Nutshell‐Derived Amines
Bibliographic record
Abstract
Abstract Waste‐derived fish oil (FO) can be epoxidized and reacted with CO2 to produce a cyclic carbonate containing material. Upon reaction with a bioderived amine, this leads to the formation of nonisocyanate polyurethane materials. The FO used is extracted from the by‐products produced at fish processing plants, including heads, bones, skin, and viscera. Three different methods are used for the epoxidation of the FO: (i) oxidation by 3‐chloroperoxybenzoic acid, (ii) oxidation by hydrogen peroxide and acetic acid, catalyzed by sulfuric acid, and (iii) oxidation by hydrogen peroxide catalyzed by formic acid. Synthesized FO epoxides are reacted with CO2 to yield FO cyclic carbonates with high conversions. The products are characterized by 1H and 13C NMR spectroscopy, IR spectroscopy, thermogravimetric analysis, and viscometry. Using a biomass‐derived amine, nonisocyanate polyurethane materials are synthesized. This process can lead to new opportunities in waste management, producing valuable materials from a resource that is otherwise underutilized.
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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".