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Record W4391530314 · doi:10.3390/fib12020017

Utilization of Novel Basalt Fiber Pellets from Micro- to Macro-Scale, and from Basic to Applied Fields: A Review on Recent Contributions

2024· review· en· W4391530314 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFibers · 2024
Typereview
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of ManitobaGovernment of ManitobaTetra Tech (Canada)Lakehead University
FundersUniversity of Manitoba
KeywordsPelletsMacroFiberScale (ratio)Materials scienceBasalt fiberBasaltNanotechnologyEngineering physicsMechanical engineeringComputer scienceAerospace engineeringEngineeringGeologyComposite materialPhysicsGeochemistry

Abstract

fetched live from OpenAlex

Fiber-reinforced cementitious composites (FRCC) are one of the leading engineering materials in the 21st century, as they offer proficiency in enhancing strength, ductility, and durability in structural engineering applications. Because the recently developed basalt fiber pellets (BFP) offer combined strands of fibers encased in a polymer matrix, they are being prevalently studied to explore new possibilities when used in brittle materials such as mortar and concrete. Hence, this paper synthesizes the intensive research efforts and contributions to this novel class of fibers conducted by the authors. Specifically, it reviews the fresh, mechanical, and durability properties of FRCC incorporating single BFP or hybrid with polyvinyl alcohol fibers and modified with slag/fly ash and nano-materials and its suitability for different field applications. In addition, the nano- and meso-scale modeling of such matrices are described. BFP significantly contributes to improving post-cracking flexural behavior by toughening the cementitious matrix and minimizing strength losses when exposed to harsh environments. All results show promising progress in the development of high-performance FRCC comprising BFP, with potential success for structural and pavement applications.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.624
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.040
GPT teacher head0.343
Teacher spread0.303 · 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