Fungal Innovation: Harnessing Mushrooms for Production of Sustainable Functional Materials
Bibliographic record
Abstract
Abstract Underutilized co‐ and by‐products are upgraded into materials with functional properties. The utilization of mushroom farming residues is investigated, specifically mushroom residues and spent mushroom substrate – whose chemical composition is determined – to produce cosmetic face masks, packaging films, and oil sorbents. Flexible mushroom sheets exhibit conformability and antioxidant activity between 82 and 94%, and better tensile strength in comparison with commercial cosmetic masks, making them suitable for such applications. Plasticization with glycerol increases the flexibility and tensile strain from ≈1 to 45% and moisture sorption from 32 to 100 wt.%. Spent mushroom substrate pulp yields stiff and strong rigid sheets with Young's moduli of 5 GPa and tensile strengths of 42 MPa. These sheets show 100% antioxidant activity, having hydrophobic behavior and oxygen barrier properties in dry conditions, and thus are promising for bioactive packaging applications. Foamed spent mushroom substrate sorbents demonstrate high affinity for both oil and water, with a water and oil uptake of 21 and 28 times their weight, respectively, while maintaining structural integrity. These properties make the foams viable as bio‐based oil sorbents, highlighting the potential of by‐products for advanced functional materials.
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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".