Surface Modification of Flax Fibers with TMCTS-Based PECVD for Improved Thermo-Mechanical Properties of PLA/Flax Fiber Composites
Bibliographic record
Abstract
Significant progress has been made in recent years in the use of atmospheric pressure plasma techniques for surface modification. This research focused on the beneficial effects of these processes on natural by-products, specifically those involving natural fiber-based materials. The study explored the deposition of hydrophobic organosilicon-like thin films onto flax fibres through plasma-enhanced chemical vapour deposition (PECVD), using tetramethylcyclotetrasiloxane (TMCTS) as the precursor. After the successful deposition of hydrophobic organosilicon-like thin films onto the flax fibres, polylactic acid (PLA) composite materials were fabricated. This fabrication process sets the stage for an in-depth analysis of the modified materials. Subsequently, these flax fabrics were subjected to meticulous characterization through scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and contact angle measurements. The results demonstrated successful TMCTS deposition on the surface which led to a complete hydrophobization of the flax fibers. Mechanical tests of the PLA/flax fibre composites revealed a significant improvement in load transfer and interfacial compatibility following the surface modification of the flax fibres. This improvement was attributed to the enhanced adhesion between the modified fibres and the PLA matrix. The findings highlight the potential of TMCTS-based PECVD as a practical surface modification technique, effectively enhancing the mechanical properties of PLA/flax fibre composites. These developments open exciting possibilities for sustainable and high-performance composite materials in various industries.
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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".