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Record W2237490445 · doi:10.1021/acs.macromol.5b01993

A Simulation Study of Phase Behavior of Double-Hydrophilic Block Copolymers in Aqueous Solutions

2015· article· en· W2237490445 on OpenAlexafffund
Jiaping Wu, Zheng Wang, Yuhua Yin, Run Jiang, Baohui Li, An‐Chang Shi

Bibliographic record

VenueMacromolecules · 2015
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsMcMaster University
FundersChangjiang Scholar Program of Chinese Ministry of EducationState Administration of Foreign Experts AffairsMinistry of Education of the People's Republic of ChinaNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsCopolymerGyroidReentrancyVolume fractionMaterials scienceAmphiphilePhase diagramPolymer chemistryMonomerPhase (matter)Annealing (glass)ThermodynamicsPhase transitionChemistryPolymerOrganic chemistryComposite materialPhysics

Abstract

fetched live from OpenAlex

The phase behavior of double-hydrophilic AB diblock copolymers in concentrated aqueous solutions is investigated using a simulated annealing technique. Phase diagrams of the system are constructed as a function of the volume fraction and concentration of the copolymer (Φ) as well as the hydrophilicity difference between the two blocks. Rich phase transition sequences, especially reentrant phase transitions, such as lamellae → gyroid → hexagonally packed cylinders → gyroid → lamellae → disorder, are observed for a given copolymer with decreasing Φ. By analyzing the variations of the average contact numbers between the A or B monomers and solvents, and of the effective volume fractions, the mechanisms of the reentrant, the order–order, and the order–disorder transitions are elucidated. The difference in hydrophilicity or in volume fraction can be used to tune the degree of swelling of the two blocks, resulting in a nonmonotonic variation of the effective volume fraction of the A (or B)-rich domain with the decrease of Φ, thus inducing the reentrant transitions. Our results are compared with those from available experiments, theory, and simulation and also with the simulation result of an amphiphilic diblock copolymer.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.047
GPT teacher head0.324
Teacher spread0.277 · 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 designSimulation or modeling
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

Citations25
Published2015
Admission routes2
Has abstractyes

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