Characterization of three‐dimensional braided polyethylene fiber–PMMA composites and influence of fiber surface treatment
Bibliographic record
Abstract
Abstract Three‐dimensional (3D) braided polyethylene (PE) fiber‐reinforced poly(methyl methacrylate) (PMMA), denoted as PE3D/PMMA, composites were prepared. Mechanical properties including flexural and impact properties, and wear resistance were tested and compared with those of the corresponding unidirectional PE fiber–PMMA (abbreviated to PEL/PMMA) composites. Both untreated and chromic acid‐treated PE fibers were used to fabricate the 3D composites in an attempt to assess the effect of chromic acid treatment on the mechanical properties of the composites. Relative changes of mechanical properties caused by fiber surface treatment were compared between the PE3D/PMMA and PEL/PMMA composites. The treated and untreated PE fibers were observed by scanning electron microscopy (SEM) and analyzed by X‐ray photoelectron spectroscope (XPS). SEM observations found that micro‐pits were created and that deeper and wider grooves were noted on the surfaces of the PE fibers. XPS analysis revealed that more hydroxyl (OH) and carboxyl (COOH) groups were formed after surface treatment. The physical and chemical changes on the surfaces of the PE fibers were responsible for the variations of the mechanical properties of the PE/PMMA composites. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 99: 949–956, 2006
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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".