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Record W2587897631 · doi:10.1021/acs.macromol.7b00078

Domain Bridging in Thermoplastic Elastomers of Star Block Copolymer

2017· article· en· W2587897631 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMacromolecules · 2017
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsUniversity of Waterloo
FundersDivision of Chemistry
KeywordsCopolymerThermoplastic elastomerBridging (networking)ElastomerMaterials scienceThermoplasticStarsPolymer scienceStar (game theory)Star polymerMoleculePolymer chemistryComposite materialBlock (permutation group theory)PolymerComputer sciencePhysicsChemistryMathematicsGeometryOrganic chemistryAstrophysics

Abstract

fetched live from OpenAlex

The performance of thermoplastic elastomers composed of block copolymers is dependent upon the molecular bridges linking together the discrete minority domains. Here we devise a strategy for calculating the bridging statistics for complex block copolymer architectures, using self-consistent field theory. The method is demonstrated on (AB) M stars with M identical diblock arms. The fraction of molecules forming bridges, ν b, is found to increase rapidly with M to values well beyond that of conventional ABA triblock copolymers. Once M is of order 10, virtually all molecules form bridges, and furthermore their arms tend to be distributed equally among neighboring minority domains. These high bridging fractions combined with the tendency of single molecules to bridge multiple domains make diblock-arm stars an excellent candidate for improved thermoplastic elastomers.

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.

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 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 score0.009
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.244
Teacher spread0.235 · 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