Assessment of Acoustic Properties of Mycelium-Based Composites Materials
Bibliographic record
Abstract
Mycelium-based composites are self-grown materials, based on agricultural residue fibers that are inoculated with fungi mycelium. The mycelium forms an interwoven 3-dimensional filamentous network, binding every fiber particle together to create a rigid, lightweight composite material without utilizing energy input or producing extra waste. Today, the increasing concern for the environmental impact of plastic or petroleum-based materials has led to a growing interest in biomaterials. Mycelium-based composites could replace current products in the packaging industry, as well as in construction (e.g., materials for thermal and acoustic insulation). Many physical properties can be tuned by controlling the fungal species, the growth conditions and the post-growth processes. In order to evaluate the sound absorption properties of mycelium-based composites made from residual hemp fiber and Ganoderma lucidum fungi, sound absorption tests were conducted in a small reverberant chamber and in an impedance tube. The results obtained are comparable to those obtained with conventional ceiling tiles on the 250 - 5000 Hz spectrum frequency band. The findings emphasize the importance of exploring bio-based materials for environmentally friendly solutions, contributing to the growing body of knowledge in sustainable acoustic engineering.
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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 | 0.001 | 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".