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Record W2075366236 · doi:10.1002/mame.200600203

Use of Nitrogen as a Blowing Agent for the Production of Fine‐Celled High‐Density Polyethylene Foams

2006· article· en· W2075366236 on OpenAlex
John W. S. Lee, Chul B. Park

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMacromolecular Materials and Engineering · 2006
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBlowing agentMaterials scienceHigh-density polyethyleneTalcExtrusionComposite materialVoid (composites)NucleationDrop (telecommunication)PorosityPressure dropPolyethyleneFoaming agentLow-density polyethylenePolyurethane

Abstract

fetched live from OpenAlex

Abstract Summary: While many experiments have been performed to examine the effects of administering CO 2 as a blowing agent in the foaming process, very few studies have investigated the use of N 2 for this purpose. In this study, foaming experiments were conducted in extrusion using HDPE as a polymeric material and N 2 as a blowing agent. Talc was used as a nucleating agent, and three different pressure‐drop rates were applied to study the effects of pressure‐drop rates on HDPE foams. The experimental results revealed that the void fraction of high‐density foams blown with N 2 was not affected by the die temperature, contrasting the situation in low‐density foams. Surprisingly, it was the cell density which determined the void fraction of high‐density foams. It was also found that the use of talc significantly increased the cell density and the void fraction of the foams and minimized the role played by the pressure‐drop rate in cell nucleation. Effect of N 2 content on the cell density of HDPE foams. magnified image Effect of N 2 content on the cell density of HDPE 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.

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 score0.001
Threshold uncertainty score0.415

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 head0.008
GPT teacher head0.187
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