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Record W3207455704 · doi:10.1002/mame.202100622

Acoustic Absorption Properties of Polystyrene‐Pyrolytic Pinus Resinosa Composite Foams Prepared by Torsion‐Induced Extrusion

2021· article· en· W3207455704 on OpenAlexaff
Ranran Jian, Peyman Shahi, Maria Semeniuk, Jing Tan, Weimin Yang, Mohini Sain

Bibliographic record

VenueMacromolecular Materials and Engineering · 2021
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of Toronto
FundersChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsMaterials scienceComposite materialComposite numberPolystyreneNucleationPyrolytic carbonExtrusionPorosityBlow moldingGlass microsphereBlowing agentPyrolysisPolymerChemical engineeringPolyurethaneMicrosphere

Abstract

fetched live from OpenAlex

Abstract A lightweight acoustic composite foams with unique sound absorption feature is reported, that is, the foam acoustic composite demonstrates surprisingly stable sound absorption performance in a wide bandwidth of frequency. The unique acoustic properties are attributed to the highly exfoliated nanolayered biocarbon nucleation, derived from the pyrolytic pinus resinosa, with tailoring the foam structure and properties. Polystyrene (PS) composite foams with porous graphitic biocarbon are obtained by sequestering recycled supercritical carbon dioxide assisted with torsion extrusion technology. Unique design concept is validated and implemented in the torsion‐induced extrusion process, with good mixing and thermal management, offering a suitable environment for the nucleation, uniform growth, and stability of the cells on the foam structures. The presence of porous graphitic nanolayered characteristics of biocarbon in the composition changes the sound insulation behavior from resonant absorber of pure PS closed cell foam to stable acoustic performance over a wide range in high frequency band (3.5–6.4 kHz), while preserving the closed cell structure. This allows the tailoring of cell structures and properties with varying renewable carbon content, so as to better adapt to a broadband sound absorption applications including absorbing panels, anechoic chamber with high accuracy and aircraft acoustic stealth technology.

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 score0.004
Threshold uncertainty score0.831

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 head0.007
GPT teacher head0.186
Teacher spread0.179 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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