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Record W1522028901 · doi:10.1002/9780470825150.ch24

Architectural Polymers, Nanostructures, and Hierarchical Structures from Block Copolymers

2011· other· en· W1522028901 on OpenAlexaff
Ian Wyman, Guojun Liu

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsQueen's University
Fundersnot available
KeywordsCopolymerMicelleMaterials sciencePolymerBlock (permutation group theory)Self-assemblyNanostructurePolymer chemistryNanotechnologyChemical engineeringChemistryComposite materialOrganic chemistryAqueous solutionGeometryMathematics

Abstract

fetched live from OpenAlex

Block copolymers self-assemble in the solid state and in block-selective solvents. In the case of a solid diblock copolymer, the minority block segregates from the majority block to form periodically spaced regular domains. The domains can take the shape of spheres, cylinders, gyroids, or lamellae, depending on the volume fraction of the minority block. In a block-selective solvent, a block copolymer self-assembles into micelles. The micellar shape is determined by the composition of the block copolymer, and the interfacial tension between the insoluble block(s) and the solvent. Also coexisting with the micelles are single-chain micelles. This article reviews our efforts in utilizing these self-assembly properties of block copolymers to prepare block copolymer architectures. These architectures include architectural polymers, nanostructures, and hierarchical structures. Two major strategies that we have used to modify the self-assembled structures of block copolymers have included directed assembly and chemical processing of the assembled structures. In directed assembly, we physically modify the self-assembly process. We combined emulsification with block copolymer assembly and created special environments, such as confined volumes or 2D spaces, for block copolymer self-assembly to take place. Through chemical processing, we modify the self-assembled structures chemically. We have been able to ‘lock in’ the assembled structures of block copolymers and/or perform selective domain degradation. After structural locking, ‘permanent’ structures such as nanostructures and architectural polymers were produced. These permanent structures could be further chemically processed or assembled to yield more complex structures, including hierarchical assemblies. We will give an overview of the strategies that we use for block copolymer architecture preparation. Reviewed in some detail are our most recent research developments, which involved the use of block copolymers as precursors for architectural polymers.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.224
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0630.000

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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
GenreOther

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

Citations2
Published2011
Admission routes1
Has abstractyes

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