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Record W2621914736 · doi:10.1002/aic.15820

Heat assisted twin screw dry granulation

2017· article· en· W2621914736 on OpenAlexaff
Y. Liu, Michael R. Thompson, K.P. O’Donnell, Salah F. Abdellah Ali

Bibliographic record

VenueAIChE Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGranulationMaterials scienceBarrel (horology)Composite materialPolymerSinteringPorosityBreakageMoistureGranule (geology)Glass transition

Abstract

fetched live from OpenAlex

A new “assisted” dry granulation method has been devised for the twin‐screw granulator. The method may be beneficial to drug preparation as it limits heat exposure to only one barrel zone, much shorter than melt granulation. Its mechanism was investigated using four placebo formulations, each containing a polymer binder with a glass transition temperature lower than 130°C. Variables of study included screw configuration, screw speed, barrel zone temperature, and moisture content. Granulated samples were characterized for size and porosity while feed powders were examined for their thermal transitions, interparticle friction, cohesion, and sintering rate. Results indicated that granule coalescence relied on melting of polymer binder in the kneading blocks by a combination of heat conducted from barrel and generated from screw speed friction. Successful granulation was possible with minimal addition of water, although varying the moisture content showed the relevance of the polymer's glass transition temperature and sintering progress. © 2017 American Institute of Chemical Engineers AIChE J , 2017

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.427

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 head0.019
GPT teacher head0.245
Teacher spread0.226 · 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 designObservational
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

Citations10
Published2017
Admission routes1
Has abstractyes

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