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Record W2330773238 · doi:10.1021/cm401472j

Fabrication of Binary Opal Lattices in Microfluidic Devices

2013· article· en· W2330773238 on OpenAlexafffund
Ali Malekpourkoupaei, Larry W. Kostiuk, D. Jed Harrison

Bibliographic record

VenueChemistry of Materials · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsNational Research Council CanadaNational Institute for NanotechnologyUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsPolystyreneMaterials scienceFabricationMicrofluidicsColloidal crystalStoichiometryNanotechnologyParticle (ecology)Colloidal silicaColloidSedimentationParticle sizeChemical engineeringOptical microscopePolymerScanning electron microscopeChemistryComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

We have studied growth and fabrication of opal lattices made from polystyrene and silica particles by an on-chip colloidal self-assembly (CSA) approach. An optical microscopy method was used to analyze the lattice growth behavior. A mathematical model was also adopted and modified to describe the growth behavior of the silica system. On the basis of these studies, silica and polystyrene systems demonstrate different growth dynamics that originate from a sedimentation process in the microfluidic chip reservoir fractionating large and small particles. Binary lattices of silica particles were fabricated by a periodic chip rotation method. The effect of particle number ratio on the opal stoichiometry was also studied for the polystyrene system. By increasing the number ratio from 2.5 to 11, different structural stoichiometries were achieved.

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 categoriesInsufficient payload (model declined to judge)
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 score0.009
Threshold uncertainty score0.999

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)0.0020.000

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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.

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

Citations20
Published2013
Admission routes2
Has abstractyes

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