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Record W1486612401 · doi:10.4271/2007-01-2187

Microcellular Ceramic Foams: Manufacturing and Study of Acoustical Properties

2007· article· en· W1486612401 on OpenAlexaff
Chunmin Wang, Chul B. Park, Noureddine Atalla

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2007
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de SherbrookeUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceCeramicComposite materialAcoustics

Abstract

fetched live from OpenAlex

A novel processing method for fabricating high porosity microcellular ceramic foams for sound absorption applications has been developed. The strategy for fabricating the ceramic foams involves: (i) forming some shapes using a mixture of preceramic polymer and expandable microspheres by a conventional ceramic forming method, (ii) foaming the compact by heating, (iii) cross-linking the foamed body, and (iv) transforming the foamed body into ceramic foams by pyrolysis. By controlling the microsphere content and that of the base elastomer, it was possible to adjust the porosity with a very high open-cell content (ranging between 43 - 95%), high microcellular cell densities (9 × 108 - 1.6 × 109 cells/cm3) and desired expansion ratios (3 - 6 folds). Sound absorption testing has been performed using ASTM C-384 standard test. The preliminary results show that ceramic foams are candidate sound absorption materials.

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 score0.002

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 integrity0.0000.000
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 head0.016
GPT teacher head0.240
Teacher spread0.223 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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