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Record W4322503240 · doi:10.3390/ma16051934

Morphological, Mechanical and Thermal Properties of Rubber Foams: A Review Based on Recent Investigations

2023· review· en· W4322503240 on OpenAlexaff
Ehsan Rostami‐Tapeh‐Esmaeil, Denis Rodrigue

Bibliographic record

VenueMaterials · 2023
Typereview
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceNatural rubberComposite materialPorosityFlexibility (engineering)ThermalElasticity (physics)Material propertiesAbrasion (mechanical)

Abstract

fetched live from OpenAlex

During recent decades, rubber foams have found their way into several areas of the modern world because these materials have interesting properties such as high flexibility, elasticity, deformability (especially at low temperature), resistance to abrasion and energy absorption (damping properties). Therefore, they are widely used in automobiles, aeronautics, packaging, medicine, construction, etc. In general, the mechanical, physical and thermal properties are related to the foam's structural features, including porosity, cell size, cell shape and cell density. To control these morphological properties, several parameters related to the formulation and processing conditions are important, including foaming agents, matrix, nanofillers, temperature and pressure. In this review, the morphological, physical and mechanical properties of rubber foams are discussed and compared based on recent studies to present a basic overview of these materials depending on their final application. Openings for future developments are also presented.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.157
GPT teacher head0.326
Teacher spread0.168 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations18
Published2023
Admission routes1
Has abstractyes

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