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Record W2315523588 · doi:10.1103/physreve.88.042501

Nematic molecular core flexibility and chiral induction

2013· article· en· W2315523588 on OpenAlexaff
Tzu-Chieh Lin, Ian R. Nemitz, Christopher J. McGrath, Christopher P. J. Schubert, Hiroshi Yokoyama, Robert P. Lemieux, Charles Rosenblatt

Bibliographic record

VenuePhysical Review E · 2013
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsQueen's University
Fundersnot available
KeywordsFlexibility (engineering)Core (optical fiber)Liquid crystalMaterials scienceMathematicsComposite material

Abstract

fetched live from OpenAlex

Electroclinic measurements, in which an applied electric field E induces a rotation Δθ ([proportional]E) of the liquid crystal director about the electric field axis in a chiral environment, were performed on several configurationally achiral liquid crystals in the presence of an imposed helical director profile. This imposed twist establishes a chiral symmetry environment for the liquid crystal. It was observed that a conformationally racemic mesogen possessing a flexible phenyl benzoate core exhibits a measurable electroclinic response in the nematic phase. On the other hand, when the phenyl benzoate mesogen is mixed with a mesogen containing a rigid, conformationally achiral core (fluorenone), or with a racemic dopant with an axially chiral core that mimics a mesogen having rigid right- and left-handed conformations (2,2'-spirobiindan-1,1'-dione), the magnitudes of the electroclinic responses were found to decrease sharply, apparently going to zero when extrapolated to the pure 2,2'-spirobiindan-1,1'-dione or fluorenone limit. (Note that neither of these additives possesses a nematic phase.). The results suggest that the flexibility of the core and its ability to deracemize conformationally in order to compensate the elastic energy cost of the imposed twist is the primary mechanism behind the observed electroclinic response.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.957

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)0.0000.001

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 head0.055
GPT teacher head0.383
Teacher spread0.328 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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