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Record W2069601505 · doi:10.1002/mame.200800060

Electromagnetic Interference (EMI) Shielding Effectiveness of PP/PS Polymer Blends Containing High Structure Carbon Black

2008· article· en· W2069601505 on OpenAlexaff
Mohammed H. Al‐Saleh, Uttandaraman Sundararaj

Bibliographic record

VenueMacromolecular Materials and Engineering · 2008
Typearticle
Languageen
FieldMaterials Science
TopicElectromagnetic wave absorption materials
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceCarbon blackPolystyreneElectromagnetic shieldingComposite numberComposite materialElectromagnetic interferencePolymer blendEMIElectrical resistivity and conductivityPolymerPhase (matter)Polymer chemistryNatural rubberCopolymerOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract The morphological, electrical resistivity (ER), and electromagnetic interference (EMI) shielding effectiveness (SE) properties of poly(propylene) (PP), polystyrene (PS), PP/PS, and PP/PS/styrene–butadiene–styrene (SBS) blends filled with 10 vol.‐% high structure carbon black (CB) were studied. For the CB/PP/PS blends, TEM and SEM observations indicated that CB is preferentially localized in the PS phase. ER and EMI SE of the CB/PP/PS and CB/PP/PS/SBS blends were bounded between those of the PS composite (lower bound) and the PP composite (upper bound). In the PP/PS volume ratio ranging from (75/25) to (25/75), ER and EMI SE of the CB‐filled blends were independent of the PP/PS volume ratio. The EMI SE obtained by the 2 mm thick plates made of 10 vol.‐% CB‐filled (100/0)–(10/90) PP/PS blends are adequate for computers shielding applications. magnified image

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 score0.004

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 head0.005
GPT teacher head0.187
Teacher spread0.182 · 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

Citations160
Published2008
Admission routes1
Has abstractyes

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