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Record W3216532741 · doi:10.1002/adem.202100985

Scalable Fabrication of Microcellular Open‐Cell Polymer Foams

2021· article· en· W3216532741 on OpenAlexaff
Raymond K. M. Chu, Lun Howe Mark, Chul B. Park

Bibliographic record

VenueAdvanced Engineering Materials · 2021
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsCanada Research ChairsUniversity of New Brunswick
Fundersnot available
KeywordsMaterials sciencePolypropyleneComposite materialThermoplasticThermosetting polymerPolymerFabricationMolding (decorative)Porosity

Abstract

fetched live from OpenAlex

Open‐cell foams are foams with porous, interconnected cellular structure. This unique structure has given open‐cell foams the versatility to be used in different types of applications including acoustics, filtration, membranes, and bioscaffolds. Conventional open‐cell polymer foams comprise mainly thermosetting and/or crosslinked materials; such materials are difficult to process and have limited end‐product recyclability. This article presents a commercially viable molding process to fabricate open‐cell foams using noncrosslinked thermoplastic polypropylene (PP). Highly open‐cell and/or reticulated structures at an open‐cell content of 84% are attained. The strategies employed in molding of PP foam with high open‐cell degree include: 1) use of mold‐opening method to achieve high void fractions; 2) reduction of cell‐wall thickness through increasing the cell densities via controlled crystallization; and 3) use of low viscosity or low melt‐strength polymer resins to promote cell‐wall opening. The molding process proposed may be extended to other semicrystalline thermoplastic materials for fabricating recyclable open‐cell foams.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.209
Teacher spread0.203 · 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 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

Citations11
Published2021
Admission routes1
Has abstractyes

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