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Record W4411139582 · doi:10.1016/j.jmrt.2025.06.009

Effects of silica-fume surface modification on polypropylene fiber-matrix interaction in cementitious composites

2025· article· en· W4411139582 on OpenAlexafffund
Jaykumar Viradiya, Rishi Gupta

Bibliographic record

VenueJournal of Materials Research and Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceSilica fumeComposite materialPolypropyleneFiberSurface modificationCementitiousMatrix (chemical analysis)CementChemical engineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.334

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.330
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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