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Record W2239787123 · doi:10.1021/acs.macromol.5b02254

Superhelices with Designed Helical Structures and Temperature-Stimulated Chirality Transitions

2015· article· en· W2239787123 on OpenAlexafffund
Chunhua Cai, Jiaping Lin, Xingyu Zhu, Shuting Gong, Xiaosong Wang, Liquan Wang

Bibliographic record

VenueMacromolecules · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsUniversity of Waterloo
FundersUniversity of WaterlooMinistry of Science and Technology of the People's Republic of ChinaMinistry of Education of the People's Republic of ChinaNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsChirality (physics)TetrahydrofuranCircular dichroismEthylene glycolChemistrySolventPolymerPhase diagramCrystallographyPolymer chemistryPhase (matter)Organic chemistryChiral symmetry

Abstract

fetched live from OpenAlex

The synthesis of multicomponent superhelices with determined chirality has been realized. By adding water to polymer solution in organic solvents (tetrahydrofuran/ N, N ′-dimethylformamide, THF/DMF), poly(γ-benzyl l -glutamate)- block -poly(ethylene glycol) (PBLG- b -PEG) are able to pack orderly around the surface of PBLG homopolymer bundles with designed helical structures, e.g., right-handed and left-handed, depending on THF/DMF ratio and temperature. A systematic investigation leads to the construction of a temperature–organic solvent composition phase diagram. Before the organic solvents were totally removed, the chirality of the assemblies can be reversibly switched using temperature stimulus. This temperature-stimulated chirality transition of polypeptide superhelices is unprecedented. Circular dichroism (CD) experiments indicated that the packing mode of pending phenyl groups from PBLG chain is responsible for the determination of the helical morphologies.

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 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 score0.012
Threshold uncertainty score0.961

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 science0.0000.000
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 head0.019
GPT teacher head0.258
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.

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

Citations52
Published2015
Admission routes2
Has abstractyes

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