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Record W2121991733 · doi:10.1002/adfm.200304338

From Hybrid Microgels to Photonic Crystals

2003· article· en· W2121991733 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

VenueAdvanced Functional Materials · 2003
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials sciencePhotonic crystalNanotechnologyPhotonicsOptoelectronics

Abstract

fetched live from OpenAlex

Abstract We have synthesized semiconductor and metal nanoparticles (NPs) in the constrained geometry of polymer microgels. We used electrostatically driven attraction between the ionic groups of the microgels and the precursor cations in the bulk liquid medium to introduce the cations in the interior of the microgel. In the second step, the cations in the microgel interior reacted with the anion (to obtain semiconductor NPs) or they were treated with a reducing agent (to obtain metal NPs). Good control over the size and the concentration of the NPs in the microgel particles was achieved by changing the composition of the corresponding microgel. The doped microgel spheres were heated at pH 4 above the volume‐transition temperature of the polymer to expel the water from the microsphere interior; then the polymer was encapsulated with a hydrophobic polymeric shell. Hybrid core–shell particles were used as the building blocks of the nanostructured material with properties of a photonic crystal.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.078
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0290.005

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 head0.020
GPT teacher head0.277
Teacher spread0.258 · 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