MétaCan
Menu
Back to cohort
Record W2345344909 · doi:10.1126/science.aad9521

Uniform patchy and hollow rectangular platelet micelles from crystallizable polymer blends

2016· article· en· W2345344909 on OpenAlexafffund
Huibin Qiu, Yang Gao, Charlotte E. Boott, Oliver E. C. Gould, Robert L. Harniman, M. J. Miles, S Webb, Mitchell A. Winnik, Ian Manners

Bibliographic record

VenueScience · 2016
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsUniversity of Toronto
FundersH2020 European Research CouncilBiotechnology and Biological Sciences Research CouncilEngineering and Physical Sciences Research CouncilMedical Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsMicelleDissolutionMaterials scienceCopolymerPolymerEtching (microfabrication)Chemical engineeringBlock (permutation group theory)NanotechnologyComposite materialChemistryGeometryOrganic chemistry

Abstract

fetched live from OpenAlex

The preparation of colloidally stable, self-assembled materials with tailorable solid or hollow two-dimensional (2D) structures represents a major challenge. We describe the formation of uniform, monodisperse rectangular platelet micelles of controlled size by means of seeded-growth methods that involve the addition of blends of crystalline-coil block copolymers and the corresponding crystalline homopolymer to cylindrical micelle seeds. Sequential addition of different blends yields solid platelet block comicelles with concentric rectangular patches with distinct coronal chemistries. These complex nano-objects can be subject to spatially selective processing that allows their disassembly to form perforated platelets, such as well-defined hollow rectangular rings. The solid and hollow 2D micelles provide a tunable platform for further functionalization and potential for a variety of applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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

Citations390
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueScienceSame topicAdvanced Polymer Synthesis and CharacterizationFrench-language works237,207