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Record W2783846544 · doi:10.1073/pnas.1717850115

Origins of low-symmetry phases in asymmetric diblock copolymer melts

2018· article· en· W2783846544 on OpenAlexafffund
Kyungtae Kim, Akash Arora, Ronald M. Lewis, Meijiao Liu, Weihua Li, An‐Chang Shi, Kevin D. Dorfman, Frank S. Bates

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsMcMaster University
FundersArgonne National LaboratoryDivision of Materials ResearchOffice of ScienceNational Natural Science Foundation of ChinaCompute CanadaNorthwestern UniversityNational Science FoundationDuPontDow Chemical CompanyUniversity of MinnesotaU.S. Department of Energy
KeywordsCopolymerSymmetry (geometry)Materials sciencePolymer scienceChemical physicsPolymer chemistryChemistryPolymerComposite materialMathematicsGeometry

Abstract

fetched live from OpenAlex

Significance We demonstrate that low-molecular weight asymmetric diblock copolymer melts can form multiple metastable liquid states at a common temperature, dependent on the processing history. Formation of ordered self-assembled micelles at low temperatures shapes the number density of the mesoscopic particles, which is preserved upon heating above the order–disorder transition temperature. Cooling returns the liquid to the same crystalline state reflecting a memory—a type of hidden symmetry—imprinted in the fluid. These surprising results are explained based on the large energetic penalty associated with fusing or fragmenting micelles in the highly structured liquid state. This work reveals concepts related to spontaneous symmetry breaking in self-assembled soft materials including surfactant-based systems.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.029
GPT teacher head0.312
Teacher spread0.282 · 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

Citations143
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicBlock Copolymer Self-AssemblyFrench-language works237,207