Effect of Fungal Deterioration on Physical and Mechanical Properties of Hemp and Flax Natural Fiber Composites
Bibliographic record
Abstract
The development and application of bio-sourced composites have been gaining wide attention, yet their deterioration due to the growth of ubiquitous microorganisms during storage/manufacturing/in-service phases is still not fully understood for optimum material selection and design purposes. In this study, samples of non-woven flax fibers, hemp fibers, and mats made of co-mingled randomly-oriented flax or hemp fiber (50%) and polypropylene fiber (50%) were subjected to 28 days of exposure to (i) no water-no fungi, (ii) water only and (iii) water along with the Chaetomium globosum fungus. Biocomposite samples were measured for weight loss over time, to observe the rate of fungal growth and the respiration of cellulose components in the fibers. Tensile testing was conducted to measure mechanical properties of the composite samples under different configurations. Scanning electron microscopy was employed to visualize fungal hyphal growth on the natural fibers, as well as to observe the fracture planes and failure modes of the biocomposite samples. Results showed that fungal growth significantly affects the dry mass as well as the tensile elastic modulus of the tested natural fiber mats and composites, and the effect depends on both the type and the length scale of fibers, as well as the exposure condition and time.
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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".