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Record W4410412502 · doi:10.3390/polym17101348

Comparison of the Performance of Basalt Fiber-Reinforced Composites Incorporating a Recyclable and a Conventional Epoxy Resin

2025· article· en· W4410412502 on OpenAlexafffund
Farid Taheri‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, S. Chowdhury, Ahmad Ghiaskar

Bibliographic record

VenuePolymers · 2025
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEpoxyComposite materialBasalt fiberMaterials scienceComposite epoxy materialFiberBasaltGeology

Abstract

fetched live from OpenAlex

resin (BR) and conventional and widely used room-cured epoxy systems (BE). Specifically, the study probes the tensile and compressive responses of the composites fabricated by vacuum-assisted resin transfer molding. Experimental results revealed that the tensile strength of basalt-Recyclamine was higher than its counterpart (464 MPa compared to 390.9 MPa). At the same time, the BR performed only marginally better under compression, with a strength of 237.7 MPa compared to 233.9 MPa for BE. However, the BR demonstrated significantly enhanced ductility reflected by its greater compressive strain capacity (3.9% compared to only 1.1%). Different microscopic analyses unveiled distinct failure mechanisms, with more progressive failure patterns observed in BR compared with the brittle fracture characteristics of the BE composite. The performance of several micromechanical models was also investigated, with their results corroborating with the experimental results with varying degrees of accuracy. The statistical analysis showed great consistency in the results, with the CoV value below 10%. Experimental results indicated that the basalt-Recyclamine composites can be considered a promising sustainable alternative to traditional polymeric resin-based systems due to their balanced mechanical performance and environmental advantages.

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)0.000
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 score0.012
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.271
Teacher spread0.258 · 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

Citations25
Published2025
Admission routes2
Has abstractyes

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