Vacuum Infusion Molding of Natural Fibre Reinforced Biobased Resin Composite
Bibliographic record
Abstract
The increasing demand in the field of bio material research for an in-depth understanding of processing phenomenon to convert it into a useful product is essential. Besides, there is inadequate information regarding the dependency between their processing mechanism and mechanical performance. The main focus of this work is to address the issues of the resin flow behavior of natural fibre in vacuum infusion molding, the determination of permeability and validation of the proposed contact angle model with experimental data. The proposed model shows greater accuracy when validated with experimental observation. The outcome of this research emphasizes the wetting mechanism and fibre network of sisal mats are the major factors that reduces 26% of permeability as compared to glass fibres. In addition, it is observed that the swelling phenomenon had a minimal influence on the permeability of the sisal fibre mat. \nThe complex phenomena occurring during wetting of natural fibres with epoxidized soybean oil (ESO) in terms of contact angle and surface energy are investigated. The fibres are treated with various reagents to improve the wetting behavior. It is noted that NaOH treatment provides considerable amount of increase in surface area of the exposed cellulose that aids in enhancement of wettability characteristics by increasing the surface energy from 18 mN/m to 23.5 mN/m while reducing the contact angle from 530 to 310. Conversely, there is a formation of virtual layer on the fibre when treated with silane and isocyanate. Moreover, isocyanate treated fibre exhibits improved wetting behaviour in terms of increase in surface energy from 18 mN/m to 25.5 mN/m when wetted with ESO.\nThe kinetics study of the curing reaction of the resin is performed by differential scanning calorimetry. A new empirical model is proposed to analyze the kinetic data obtained experimentally. The results highlighted that the proposed model attained significant improvement to predict the experimental cure kinetic data qualitatively and quantitatively. The addition of 30% ESO in the conventional system increases the activation energy of the system up to 108 kJ/mol. The effect of the surface treatments of natural fibre, fibre loading direction, and resin flow direction on the tensile properties of developed composites are investigated. The longitudinal tensile strength of developed composites demonstrated a 7-8 fold increment, as compared to the transverse direction tensile strength. The flow along the fibre provides 10% increment in tensile strength due to higher permeability.
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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".