Extraction, Applications and Characterization of Plant Fibers
Bibliographic record
Abstract
During the second half of the twentieth century, industrial and scientific interests in plant fibers (PFs) have resulted in their resounding comeback as engineering materials. This chapter is concerned with the characterization of PF materials. Good knowledge of the properties of these materials is essential for safe design of the related structures. Bast fibers that are collected from the phloem surrounding the stem of certain dicotyledonous plants, for instance, are among the most used, owing to their higher tensile strength. However, for an optimum utilization of PFs, a relevant assessment of their physico-chemical and mechanical properties is very crucial. As it is now well established, PFs’ properties are largely influenced by their hierarchic composite microstructure and their viscoelastic behavior. This book chapter focuses on the presentation of various experimental approaches used to characterize the elastic and viscoelastic behaviors of plant fibers. Consideration of their blending in sheet form and relevant mechanical properties will also be of interest.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".