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Record W1502898376 · doi:10.5539/mas.v9n7p121

Preparation of Polystyrene Spheres Using Surfactant-Free Emulsion Polymerization

2015· article· en· W1502898376 on OpenAlexvenueno aff
F. T., Restu Mulya Dewa, Karinda Quarta, W. Widiyastuti, Sugeng Winardi

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolystyreneStyreneDispersityMaterials scienceEmulsion polymerizationMonomerSPHERESPolymer chemistryScanning electron microscopeChemical engineeringCopolymerPolymerizationMixing (physics)Composite materialPolymer

Abstract

fetched live from OpenAlex

Polystyrene spheres have been synthesized using potassium persulphate (KPS) as initiators without using anysurfactant or stabilizing agent. Simple mixing method was used to synthesize styrene monomer into polystyrenespheres. The influences of mixing time, ammount of styrene monomers, and ammount of initiators were studiedin this research. Size measurement and its distribution were analyzed by Scanning Electron Microscopy (SEM).Monodisperse spheres and verry narrow size distribution are expected in this research. The results showed thatthe most optimum time to synthesize styrene monomer into polystyrene latex is 6 hours, where biggest and mostuniform spheres size were obtained. Meanwhile when ammount of styrene monomers were increased, thediameter of polystyrene spheres were also increased. The biggest and most uniform polystyrene spheres diameterwas shown by 14% volume ratio of styrene monomer. For initiators influence, the smaller diameter ofpolystyrene spheres were obtained for 0.2 gram KPS than in 0.05 gram KPS. Polystyrene spheres using 0.05gram KPS also has more uniform size than in 0.2 gram.

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)0.001
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 score0.093
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.050
GPT teacher head0.334
Teacher spread0.284 · 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 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

Citations12
Published2015
Admission routes1
Has abstractyes

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