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Record W4315490953 · doi:10.1021/acs.macromol.2c02086

Self-Assembly of Gyroid-Forming Diblock Copolymers under Spherical Confinement

2023· article· en· W4315490953 on OpenAlexaff
Yen-Ting Juan, Yu-Fang Lai, Xingye Li, Tsung-Cheng Tai, Ching-Hsun Lin, Chih‐Feng Huang, Baohui Li, An‐Chang Shi, Han‐Yu Hsueh

Bibliographic record

VenueMacromolecules · 2023
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsMcMaster University
FundersMinistry of Science and Technology, TaiwanMinistry of Education
KeywordsGyroidCopolymerMaterials sciencePolystyreneSelf-assemblyDewettingAcrylateSPHERESPolymerNanotechnologyChemical engineeringPolymer chemistryComposite materialThin film

Abstract

fetched live from OpenAlex

The self-assembly of gyroid-forming diblock copolymers (diBCPs) confined in spherical cavities was systematically investigated by simulations and experiments. The Monte Carlo simulations were carried out on the single-site bond fluctuation model of two gyroid-forming diBCPs of different volume fractions using the simulated annealing method. The experimental study was performed on gyroid-forming poly(styrene)- b -poly(lactic acid) diBCPs confined in spherical cavities. The cavities were fabricated through the assembly of polystyrene colloids to form opal structures, followed by replacement to form inverse opal structures. The surface of the cavities was composed of hydrophobic polyurethane acrylate and hydrophilic SiO 2, providing confining surfaces with a different preference for specific polymeric blocks. It was observed from both the experiments and simulation that, depending on the conditions of spherical confinement, a rich array of nanostructures was self-assembled from the gyroid-forming diBCPs. The morphological predictions of simulations are qualitatively consistent with the experimental observations. The self-assembled structures depend sensitively on the surface selectivity and the degree of confinement quantified by the ratio D / L 0, where D and L 0 are the spherical diameter and period of the equilibrium gyroid phase, respectively. The formed nanostructured self-supporting spheres have considerable potential for applications in drug release, catalysts, optoelectronic devices, filters, and other 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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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

Citations14
Published2023
Admission routes1
Has abstractyes

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