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Record W2765307438 · doi:10.1021/acsmacrolett.7b00756

Nonclassical Spherical Packing Phases Self-Assembled from AB-Type Block Copolymers

2017· article· en· W2765307438 on OpenAlexafffund
Weihua Li, Chao Duan, An‐Chang Shi

Bibliographic record

VenueACS Macro Letters · 2017
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsCopolymerMaterials scienceSelf-assemblyMorphology (biology)Phase (matter)Block (permutation group theory)Chemical physicsNanotechnologyPolymerChemistryGeometryComposite material

Abstract

fetched live from OpenAlex

Among the various ordered morphologies self-assembled from block copolymers, the spherical packing phases are particularly interesting because they resemble the familiar atomic crystals. The commonly observed spherical morphology of block copolymers is the body-centered-cubic phase. Recently, a number of novel spherical packing phases, i.e., the complex Frank-Kasper phases originally obtained in metallic alloys, have been observed in block copolymer melts. Theoretical studies have revealed that conformational asymmetry of the different blocks provides a key mechanism to stabilize the Frank-Kasper phases. Furthermore, local segregation of different copolymers in blends of diblock copolymers and copolymer architectures provides additional mechanisms to enhance the stability of the complex ordered phases. In this Viewpoint we summarize recent advances in our understanding of the formation of the nonclassical spherical packing phases in AB-type block copolymers, emphasizing the formation mechanisms of these fascinating complex ordered structures.

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 head0.015
GPT teacher head0.268
Teacher spread0.253 · 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

Citations117
Published2017
Admission routes2
Has abstractyes

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Same venueACS Macro LettersSame topicBlock Copolymer Self-AssemblyFrench-language works237,207