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Record W2033286369 · doi:10.1021/ie060105w

A Microcellular Foaming Simulation System with a High Pressure-Drop Rate

2006· article· en· W2033286369 on OpenAlex

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

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDrop (telecommunication)Pressure dropMaterials sciencePolystyreneDrop impactNucleationBubbleBlowing agentExpanded polystyreneComposite materialPolymerThermodynamicsMechanicsComputer science

Abstract

fetched live from OpenAlex

In this paper, we undertook an experimental and theoretical analysis of the pressure-drop behaviors of a batch foaming system with a visualization window that was designed for microcellular foaming simulation. A polystyrene (PS)−CO 2 system was used in the experiment and analysis. The maximum pressure-drop rate achievable was 2.5 GPa/s from the designed system. Some experimental simulation results at high pressure-drop rates and at low pressure-drop rates are also discussed. We observed that the application of a higher pressure-drop rate results in a higher cell density (and, thereby, a smaller cell size) for plastic foams. This confirms that the pressure-drop rate is one of the most important parameters to control the cell density of plastic foams. In addition, the results show that the content of the blowing agent (CO 2 ) dissolved into a given polymer has a significant effect on bubble nucleation and growth.

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)0.001
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 score0.058
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.030
GPT teacher head0.261
Teacher spread0.231 · 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