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Record W2156808896 · doi:10.1039/b906626h

Multiple modular microfluidic (M3) reactors for the synthesis of polymer particles

2009· article· en· W2156808896 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

VenueLab on a Chip · 2009
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicrofluidicsDispersityPolymerCoalescence (physics)Materials scienceModular designPolymerizationFabricationMicroreactorNanotechnologyChemical engineeringChemistryPolymer chemistryComputer scienceComposite materialOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

We report a study of the continuous generation of polymer particles in parallel multiple modular microfluidic (M3) reactors. Each module consisted of sixteen parallel microfluidic reactors comprising emulsification and polymerization compartments. We identified and minimized the effects of the following factors that could result in the broadening of the distribution of sizes of the particles synthesized in the M3 reactors, in comparison with an individual microfluidic reactor: (i) the fidelity in the fabrication of multiple microfluidic droplet generators; (ii) the crosstalk between parallel droplet generators sharing liquid supply sources; and (iii) the coalescence of precursor droplets and/or partly polymerized polymer particles. Our results show that the M3 reactors can produce polymer microgel particles with polydispersity not exceeding 5% at a productivity of approximately 50 g/h.

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 score0.128
Threshold uncertainty score0.387

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 head0.015
GPT teacher head0.230
Teacher spread0.215 · 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