Effects of silica-fume surface modification on polypropylene fiber-matrix interaction in cementitious composites
Bibliographic record
Abstract
ABSTRACT The fiber-matrix interface plays a pivotal role in determining the mechanical performance of fiber-reinforced composites. However, achieving optimal interfacial bonding remains challenging, particularly for synthetic fibers like polypropylene (PP), due to their inherently smooth surface and low chemical affinity to cementitious matrices. To further improve PP fiber-matrix interface properties, the current study evaluates the effectiveness of three novel surface treatments using silica-fume surface coating methods developed at the University of Victoria—adhesive dry coating, adhesive wet coating, and a non-adhesive heat coating. The impact of these surface modifications on fiber-matrix adhesion was assessed through contact angle measurements, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS/EDX), and micro-hardness testing. Mechanical performance was further evaluated using single-fiber pull-out, flexural, and compressive strength tests. SEM, EDX, and micro-hardness results confirmed that silica-fume from the coatings reacts with portlandite, significantly improving the interfacial transition zone (ITZ) within the first 40 μm from the fiber edge. Samples treated with adhesive dry coating and adhesive wet coating exhibited 96% and 31% higher overall energy absorption in pull-out tests, respectively, compared to untreated fibers. Furthermore, all coating methods nearly doubled post-crack energy absorption in flexural tests. Samples containing fibers treated with non-adhesive heat coating demonstrated the most pronounced effect among the surface treatments, resulting in 857% higher energy absorption (compared to untreated fiber samples) under pull-out loading, leading to fiber fracture failure. In these samples, the failure mechanism involved post-peak softening followed by strain hardening to a perfectly plastic response until fiber fracture. Based on mechanical and microstructural evaluations of the present study, non-adhesive heat coating method emerged as the most effective surface treatment, demonstrating superior fiber-matrix bonding and enhanced composite performance.
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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".